bibliography.bib

@article{Larsen1996,
  abstract = {This article describes the Cellular APplied to ITS Tracking and Location ( CAPITAL) ITS Operational Test. The goals of the project were 1) to determine if the use of cellular telephone technologies provides an accurate and cost-effective means of wide area traffic surveillance, and, 2) to determine if vehicle location information from cellular phone- equipped probe vehicles can be effectively integrated into a real-time traffic control system for regional traffic management or traveler information purposes.},
  author = {Larsen, Robert},
  journal = {Traffic Technology International},
  pages = {46--50},
  title = {{Using Cellular Phones As Traffic Probes}},
  url = {https://trid.trb.org/view/642236},
  year = {1996}
}
@techreport{White2000,
  author = {White, J and Quick, J},
  title = {{Using cellular phone location data for origin destination matrix estimation}},
  institution = {TRL, UK},
  year = {2000}
}
@article{ccolak2015analyzing,
  title = {Analyzing cell phone location data for urban travel: current methods, limitations, and opportunities},
  author = {{\c{C}}olak, Serdar and Alexander, Lauren P and Alvim, Bernardo G and Mehndiratta, Shomik R and Gonz{\'a}lez, Marta C},
  journal = {Transportation research record: Journal of the transportation research board},
  volume = {2526},
  pages = {126--135},
  year = {2015},
  publisher = {Transportation Research Board of the National Academies}
}
@techreport{Herrera2018,
  author = {Herrera, Andrea and Razmilic, Slaven},
  title = {{Movilidad urbana: Santiago no es Chile (Urban Mobility: Santiago is not Chile.)}},
  institution = {Development Bank of Latin America},
  url = {http://scioteca.caf.com/handle/123456789/414},
  year = {2018}
}
@article{Vasconcellos2010,
  author = {Vasconcellos, E.},
  isbn = {9789806810600},
  journal = {CAF},
  keywords = {Ambiente,Equidad e inclusi{\'{o}}n social,Infraestructura,Log{\'{i}}stica,Movilidad urbana,Transporte,book},
  pages = {204},
  publisher = {CAF},
  title = {{An{\'{a}}lisis de la movilidad urbana. Espacio, medio
                  ambiente y equidad (Analysis of urban
                  mobility. Space, environment and equality)}},
  url = {http://scioteca.caf.com/handle/123456789/414  www.caf.com/publicaciones},
  year = {2010}
}
@article{mowshowitz2002,
  abstract = {Biased search results on, for example, consumer product information illustrate a general problem of considerable social importance. The Web is replacing the traditional repositories that individuals and organizations turn to for the information needed to solve problems and make decisions. Search engines are gateways that mediate between users and the billions of pages on the Web, essentially acting as automated reference librarians. Users need to be aware of potential bias in search engine results to enable them either to seek alternative sources, (e.g., other search engines) or to hedge conclusions based on the results. Presents an operational definition of search engine bias, describes and illustrates a system for measuring bias, and presents a statistical analysis designed to demonstrate the utility of the measure.},
  author = {Mowshowitz, Abbe and Kawaguchi, Akira},
  doi = {10.1145/567498.567527},
  isbn = {00010782},
  issn = {00010782},
  journal = {Communications of the ACM},
  month = {may},
  number = {9},
  pages = {56--60},
  title = {{Bias on the web}},
  url = {http://dl.acm.org/ft{\_}gateway.cfm?id=567527{\&}type=html},
  volume = {45},
  year = {2002}
}
@article{Baeza-Yates2018,
  author = {Baeza-Yates, Ricardo},
  doi = {10.1145/3209581},
  issn = {00010782},
  journal = {Communications of the ACM},
  month = {may},
  number = {6},
  pages = {54--61},
  title = {{Bias on the Web}},
  url = {http://dl.acm.org/citation.cfm?doid=3229066.3209581},
  volume = {61},
  year = {2018}
}
@article{White2002,
  abstract = {Traffic origin destination data is one of the most important pieces of information required for effective network management and strategic planning. Origin destination (OD) matrices provide an estimate of the number of vehicles travelling between points on a network over a given period of time. Accurate origin destination matrices are required in assignment models, but have a wide variety of other uses. At TRL both the assignment model CONTRAM8 and the microscopic simulation model SISTM require OD matrices as input, as do almost all existing traffic models. For future applications, the Highways Agency are likely to require a national OD matrix, covering the trunk road network in the UK},
  author = {White, Jonna and Wells, Ivan},
  doi = {10.1049/cp:20020200},
  isbn = {0 85296 746 2},
  issn = {0537-9989},
  journal = {Road Transport Information and Control},
  number = {March},
  pages = {19--21},
  publisher = {IEE},
  title = {{Extracting Origin Destination Information from mobile phone data}},
  url = {http://digital-library.theiet.org/content/conferences/10.1049/cp{\_}20020200},
  volume = {486},
  year = {2002}
}
@inproceedings{Messias:2017:WMH:3106426.3106472,
  author = {Messias, Johnnatan and Vikatos, Pantelis and Benevenuto, Fabr\'{\i}cio},
  title = {White, Man, and Highly Followed: Gender and Race Inequalities in {Twitter}},
  booktitle = {Proceedings of the International Conference on Web Intelligence},
  series = {WI '17},
  year = {2017},
  isbn = {978-1-4503-4951-2},
  location = {Leipzig, Germany},
  pages = {266--274},
  numpages = {9},
  url = {http://doi.acm.org/10.1145/3106426.3106472},
  doi = {10.1145/3106426.3106472},
  acmid = {3106472},
  publisher = {ACM},
  address = {New York, NY, USA}
}
@inproceedings{Wang:2013:GTA:2470654.2470659,
  author = {Wang, Yi-Chia and Burke, Moira and Kraut, Robert E.},
  title = {Gender, Topic, and Audience Response: An Analysis of User-generated Content on Facebook},
  booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
  series = {CHI '13},
  year = {2013},
  isbn = {978-1-4503-1899-0},
  location = {Paris, France},
  pages = {31--34},
  numpages = {4},
  url = {http://doi.acm.org/10.1145/2470654.2470659},
  doi = {10.1145/2470654.2470659},
  acmid = {2470659},
  publisher = {ACM},
  address = {New York, NY, USA},
  keywords = {computer-mediated communication, facebook, gender, natural language analysis, social networking sites, topics}
}
@techreport{Hausmann2017,
  abstract = {The Global Gender Gap Index was first introduced by the World Economic Forum in 2006 as a framework for capturing the magnitude of gender-based disparities and tracking their progress over time. The Index benchmarks national gender gaps on economic, education, health and political criteria, and provides country rankings that allow for effective comparisons across regions and income groups. The rankings are designed to create global awareness of the challenges posed by gender gaps and the opportunities created by reducing them. The methodology and quantitative analysis behind the rankings are intended to serve as a basis for designing effective measures for reducing gender gaps},
  publisher = {{arXiv}},
  archiveprefix = {arXiv},
  number = {arXiv.1011.1669v3},
  author = {Hausmann, Ricardo and Tyson, Laura D},
  institution = {World Economic Forum},
  eprint = {arXiv:1011.1669v3},
  isbn = {9789295044098},
  issn = {0192-513X},
  pages = {361},
  pmid = {25246403},
  title = {{The Global Gender Gap Report 2017}},
  url = {https://www.weforum.org/reports/the-global-gender-gap-report-2017 http://www3.weforum.org/docs/WEF{\_}GGGR{\_}2017.pdf{\%}0Ahttp://www3.weforum.org/docs/WEF{\_}GGGR{\_}2017.pdf{\%}0Ahttp://www3.weforum.org/docs/WEF{\_}GGGR{\_}2017.pdf{\%}0Ahttps://www.weforum.org/reports/the-global-gender-gap-report-2017},
  year = {2017}
}
@book{zeran2018,
  editor = {Zer\'an, Faride},
  title = {{Mayo feminista. La rebelión contra el patriarcado
                  (Feminist May: the rebellion against patriarchy)}},
  publisher = {{LOM Ediciones}},
  year = {2018}
}
@article{Garcia2018,
  abstract = {Online social media are information resources that can
                  have a transformative power in society. While the
                  Web was envisioned as an equalizing force that
                  allows everyone to access information, the digital
                  divide prevents large amounts of people from being
                  present online. Online social media, in particular,
                  are prone to gender inequality, an important issue
                  given the link between social media use and
                  employment. Understanding gender inequality in
                  social media is a challenging task due to the
                  necessity of data sources that can provide
                  large-scale measurements across multiple
                  countries. Here, we show how the Facebook Gender
                  Divide (FGD), a metric based on aggregated
                  statistics of more than 1.4 billion users in 217
                  countries, explains various aspects of worldwide
                  gender inequality. Our analysis shows that the FGD
                  encodes gender equality indices in education,
                  health, and economic opportunity. We find gender
                  differences in network externalities that suggest
                  that using social media has an added value for
                  women. Furthermore, we find that low values of the
                  FGD are associated with increases in economic gender
                  equality. Our results suggest that online social
                  networks, while suffering evident gender imbalance,
                  may lower the barriers that women have to access to
                  informational resources and help to narrow the
                  economic gender gap.},
  author = {Garcia, David and {Mitike Kassa}, Yonas and Cuevas, Angel and Cebrian, Manuel and Moro, Esteban and Rahwan, Iyad and Cuevas, Ruben},
  doi = {10.1073/pnas.1717781115},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  keywords = {Facebook,development,gender divide,inequality,social media},
  month = {jul},
  number = {27},
  pages = {6958--6963},
  pmid = {29921703},
  publisher = {National Academy of Sciences},
  title = {{Analyzing gender inequality through large-scale Facebook advertising data}},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/29921703 http://www.pnas.org/lookup/doi/10.1073/pnas.1717781115},
  volume = {115},
  year = {2018}
}
@inproceedings{White2004,
  abstract = {The Department for Transport (DfT) in the UK is evaluating the process of obtaining traffic statistics such as those collected in the National Travel Survey and the traffic census. Alongside traditional methods, such as surveys and loop data, mobile phone data can be used to support and complete the existing methods. As well as considering the potential of ITS to compile traffic statistics, the DfT is also interested in its applicability to the measurement of road freight (HGV and LGV) activity, particularly origins and destinations data. In 1998, TRL was commissioned by the Highways Agency to conduct research into the feasibility of using mobile phone location data to obtain traffic information, in particular origin-destination (OD) information which would provide the core data required by many transportation simulation models including SATURN and SISTM. The results of the research are described in several documents, including White and Quick (2000) and White and Wells (2002). The research found that it was feasible to obtain OD information from mobile phone location data, as well as other forms of traffic information such as journey times and speeds. Routeing information was also extractable. TRL developed an algorithm to analyse anonymous billing data, kindly provided by BTCellnet, now O2. The paper provides an update on the previous work and focuses on the use of mobile phone data for the Department for Transport's requirements.},
  author = {White, J. and Quick, J. and Philippou, P.},
  booktitle = {12th IEEE Int. Conf. on Road Transport Information and Control},
  doi = {10.1049/cp:20040048},
  isbn = {0 86341 386 2},
  keywords = {Department for Transport,ITS,SATURN,SISTM,automated highways,journey times,mobile handsets,mobile phone data,mobile phone location data,origin-destination information,position control,road freight activity,routeing information,traffic information,traffic statistics,transportation simulation models},
  pages = {321--325},
  publisher = {IEE},
  title = {{The use of mobile phone location data for traffic information}},
  url = {http://ieeexplore.ieee.org/xpls/abs{\_}all.jsp?arnumber=1341767},
  year = {2004}
}
@inproceedings{Halepovic2005,
  abstract = {The demand for cellular data networks is expected to increase with 3G and beyond technologies accompanied by high-bandwidth consumer services, such as wireless video and camera phones. User mobility affects quality of service, and makes capacity planning more difficult. This paper presents an analysis of user mobility patterns based on data traffic traces from a major regional CDMA2000 cellular network. We find low overall mobility in the network, power-law characteristics in user mobility profiles, and weak correlations between call activity and mobility levels for individual users. We also find that users concentrate their activity in a "home cell" with frequent shorter trips to other locations in the network. Based on the empirical findings, we develop and parameterize a model of cellular data user mobility and show its practical use in simulation.},
  address = {New York, New York, USA},
  author = {Halepovic, Emir and Williamson, Carey},
  booktitle = {Proceedings of the 2nd ACM international workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks  - PE-WASUN '05},
  doi = {10.1145/1089803.1089969},
  isbn = {1595931821},
  pages = {71},
  publisher = {ACM Press},
  title = {{Characterizing and modeling user mobility in a cellular data network}},
  url = {http://portal.acm.org/citation.cfm?doid=1089803.1089969},
  year = {2005}
}
@article{Munnukka2005,
  abstract = {The study concentrated on studying how mobile service customers perceive the prices, whether customers differ in their price sensitivity levels, and if customers' price sensitivity levels be accurately predicted. For these purposes, mobile service customers have been divided into three segments: 1. mobile segment, 2. combined segment, and 3. fixed-line segment. Based on the literature review, five hypotheses were proposed, which were expected to explain significantly the differences in variances of price sensitivities in the three customer segments. It was discovered that mobile service customers differ significantly in their price sensitivity levels; customers with moderate usage of mobile services are least price sensitive, while intensive and low-end users are most sensitive to price changes. Important was also the notion that customers' price perceptions and innovativeness levels were accurate indicators of their price sensitivity.},
  author = {Munnukka, Juha},
  doi = {10.1108/10610420510583761},
  isbn = {1061042081},
  issn = {10610421},
  journal = {Journal of Product and Brand Management},
  keywords = {Finland,Mobile communication systems,Pricing,Surveys},
  month = {jan},
  number = {1},
  pages = {65--73},
  title = {{Dynamics of price sensitivity among mobile service customers}},
  url = {http://www.emeraldinsight.com/doi/10.1108/10610420510583761},
  volume = {14},
  year = {2005}
}
@article{Ratti2006,
  abstract = {The technology for determining the geographic location of cell phones and other hand-held devices is becoming increasingly available. It is opening the way to a wide range of applications, collectively referred to as Location Based Services (LBS), that are primarily aimed at individual users. However, if deployed to retrieve aggregated data in cities, LBS could become a powerful tool for urban analysis. This paper aims to review and introduce the potential of this technology to the urban planning community. In addition, it presents the ‘Mobile Landscapes' project: an application in the metropolitan area of Milan, Italy, based on the geographical mapping of cell phone usage at different times of the day. The results enable a graphic representation of the intensity of urban activities and their evolution through space and time. Finally, a number of future applications are discussed and their potential for urban studies and planning is assessed.},
  author = {Ratti, Carlo and Frenchman, Dennis and Pulselli, Riccardo Maria and Williams, Sarah},
  journal = {Environment and Planning B: Planning and Design},
  doi = {10.1068/b32047},
  isbn = {0265-8135},
  issn = {02658135},
  month = {oct},
  number = {5},
  pages = {727--748},
  title = {{Mobile landscapes: Using location data from cell phones for urban analysis}},
  url = {http://journals.sagepub.com/doi/10.1068/b32047},
  volume = {33},
  year = {2006}
}
@article{Eagle2006,
  abstract = {We introduce a system for sensing complex social systems with data collected from 100 mobile phones over the course of 9 months. We demonstrate the ability to use standard Bluetooth-enabled mobile telephones to measure information access and use in different contexts, recognize social patterns in daily user activity, infer relationships, identify socially significant locations, and model organizational rhythms.},
  author = {Eagle, Nathan and Pentland, Alex},
  doi = {10.1007/s00779-005-0046-3},
  isbn = {1617-4909$\backslash$r1617-4917},
  issn = {16174909},
  journal = {Personal and Ubiquitous Computing},
  keywords = {Bluetooth,Complex social systems,Mobile phones,User modeling,Wearable computing},
  month = {may},
  number = {4},
  pages = {255--268},
  pmid = {8523550827479701167},
  title = {{Reality mining: Sensing complex social systems}},
  url = {http://link.springer.com/10.1007/s00779-005-0046-3},
  volume = {10},
  year = {2006}
}
@article{Rouvinen2006,
  abstract = {Factors determining the diffusion of digital mobile telephony across developed and developing countries are studied with the aid of a Gompertz model. After controlling for other factors, the speed of diffusion per se is not significantly different between the two groups of countries. Standards competition hinders and market competition promotes diffusion in both groups. Various factors are, however, more important in a developing country context: having a large potential user base, accumulating network effects, being open, commanding a high (non-telecom) technological level, and introducing innovation(s) complementing mobile telephony. Late entrants experience faster diffusion promoting cross-country convergence. {\textcopyright} 2005 Elsevier Ltd. All rights reserved.},
  author = {Rouvinen, Petri},
  doi = {10.1016/j.telpol.2005.06.014},
  isbn = {0308-5961},
  issn = {03085961},
  journal = {Telecommunications Policy},
  keywords = {Developing countries,Gompertz model,Mobile telephony,Technology diffusion},
  month = {feb},
  number = {1},
  pages = {46--63},
  title = {{Diffusion of digital mobile telephony: Are developing countries different?}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0308596105001059},
  volume = {30},
  year = {2006}
}
@misc{Ratti2006a,
  abstract = {The technology for determining the geographic location of cell phones and other hand-held devices is becoming increasingly available. It is opening the way to a wide range of applications, collectively referred to as Location Based Services (LBS), that are primarily aimed at individual users. However, if deployed to retrieve aggregated data in cities, LBS could become a powerful tool for urban analysis. This paper aims to review and introduce the potential of this technology to the urban planning community. In addition, it presents the ‘Mobile Landscapes' project: an application in the metropolitan area of Milan, Italy, based on the geographical mapping of cell phone usage at different times of the day. The results enable a graphic representation of the intensity of urban activities and their evolution through space and time. Finally, a number of future applications are discussed and their potential for urban studies and planning is assessed.},
  author = {Ratti, Carlo and Frenchman, Dennis and Pulselli, Riccardo Maria and Williams, Sarah},
  booktitle = {Environment and Planning B: Planning and Design},
  doi = {10.1068/b32047},
  isbn = {0265-8135},
  issn = {02658135},
  month = {oct},
  number = {5},
  pages = {727--748},
  title = {{Mobile landscapes: Using location data from cell phones for urban analysis}},
  url = {http://journals.sagepub.com/doi/10.1068/b32047},
  volume = {33},
  year = {2006}
}
@article{Brockmann2006,
  abstract = {The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronise populations of interacting species, stabilise them, and diversify gene pools [1-3]. Human travelling, e.g. is responsible for the geographical spread of human infectious disease [4-9]. In the light of increasing international trade, intensified human mobility and an imminent influenza A epidemic [10] the knowledge of dynamical and statistical properties of human travel is thus of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Based on a comprehensive dataset of over a million individual displacements we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale free random walks known as Levy flights. Secondly, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails which attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two parameter continuous time random walk model to a surprising accuracy and conclude that human travel on geographical scales is an ambivalent effectively superdiffusive process.},
  archiveprefix = {arXiv},
  arxivid = {cond-mat/0605511},
  author = {Brockmann, D. and Hufnagel, L. and Geisel, T.},
  doi = {10.1038/nature04292},
  eprint = {0605511},
  isbn = {1476-4687},
  issn = {14764687},
  journal = {Nature},
  month = {jan},
  number = {7075},
  pages = {462--465},
  pmid = {16437114},
  primaryclass = {cond-mat},
  title = {{The scaling laws of human travel}},
  url = {http://www.nature.com/articles/nature04292},
  volume = {439},
  year = {2006}
}
@inproceedings{Nanavati2006,
  abstract = {With ever growing competition in telecommunications markets, operators have to increasingly rely on business intelligence to offer the right incentives to their customers. Toward this end, existing approaches have almost solely focussed on the individual behaviour of customers. Call graphs, that is, graphs induced by people calling each other, can allow telecom operators to better understand the interaction behaviour of their customers, and potentially provide major insights for designing effective incentives.In this paper, we use the Call Detail Records of a mobile operator from four geographically disparate regions to construct call graphs, and analyse their structural properties. Our findings provide business insights and help devise strategies for Mobile Telecom operators. Another goal of this paper is to identify the shape of such graphs. In order to do so, we extend the well-known reachability analysis approach with some of our own techniques to reveal the shape of such massive graphs. Based on our analysis, we introduce the Treasure-Hunt model to describe the shape of mobile call graphs. The proposed techniques are general enough for analysing any large graph. Finally, how well the proposed model captures the shape of other mobile call graphs needs to be the subject of future studies.},
  address = {New York, New York, USA},
  author = {Nanavati, Amit A. and Gurumurthy, Siva and Das, Gautam and Chakraborty, Dipanjan and Dasgupta, Koustuv and Mukherjea, Sougata and Joshi, Anupam},
  booktitle = {Proceedings of the 15th ACM international conference on Information and knowledge management  - CIKM '06},
  doi = {10.1145/1183614.1183678},
  isbn = {1595934332},
  pages = {435},
  publisher = {ACM Press},
  title = {{On the structural properties of massive telecom call graphs}},
  url = {http://portal.acm.org/citation.cfm?doid=1183614.1183678},
  year = {2006}
}
@article{Hill2006,
  abstract = {Network-based marketing refers to a collection of marketing techniques that take advantage of links between consumers to increase sales. We concentrate on the consumer networks formed using direct interactions (e.g., communications) between consumers. We survey the diverse literature on such marketing with an emphasis on the statistical methods used and the data to which these methods have been applied. We also provide a discussion of challenges and opportunities for this burgeoning research topic. Our survey highlights a gap in the literature. Because of inadequate data, prior studies have not been able to provide direct, statistical support for the hypothesis that network linkage can directly affect product/service adoption. Using a new data set that represents the adoption of a new telecommunications service, we show very strong support for the hypothesis. Specifically, we show three main results: (1) ``Network neighbors''--those consumers linked to a prior customer--adopt the service at a rate 3--5 times greater than baseline groups selected by the best practices of the firm's marketing team. In addition, analyzing the network allows the firm to acquire new customers who otherwise would have fallen through the cracks, because they would not have been identified based on traditional attributes. (2) Statistical models, built with a very large amount of geographic, demographic and prior purchase data, are significantly and substantially improved by including network information. (3) More detailed network information allows the ranking of the network neighbors so as to permit the selection of small sets of individuals with very high probabilities of adoption.},
  archiveprefix = {arXiv},
  arxivid = {math/0606278},
  author = {Hill, Shawndra and Provost, Foster and Volinsky, Chris},
  doi = {10.1214/088342306000000222},
  eprint = {0606278},
  isbn = {0883423060000},
  issn = {0883-4237},
  journal = {Statistical Science},
  month = {may},
  number = {2},
  pages = {256--276},
  pmid = {21444588},
  primaryclass = {math},
  title = {{Network-Based Marketing: Identifying Likely Adopters via Consumer Networks}},
  url = {http://projecteuclid.org/euclid.ss/1154979826},
  volume = {21},
  year = {2006}
}
@article{Onnela2007,
  abstract = {Electronic databases, from phone to emails logs, currently provide detailed records of human communication patterns, offering novel avenues to map and explore the structure of social and communication networks. Here we examine the communication patterns of millions of mobile phone users, allowing us to simultaneously study the local and the global structure of a society-wide communication network. We observe a coupling between interaction strengths and the network's local structure, with the counterintuitive consequence that social networks are robust to the removal of the strong ties, but fall apart following a phase transition if the weak ties are removed. We show that this coupling significantly slows the diffusion process, resulting in dynamic trapping of information in communities, and find that when it comes to information diffusion, weak and strong ties are both simultaneously ineffective.},
  archiveprefix = {arXiv},
  arxivid = {physics/0610104},
  author = {Onnela, J. -P. and Saramaki, J. and Hyvonen, J. and Szabo, G. and Lazer, D. and Kaski, K. and Kertesz, J. and Barabasi, A. -L.},
  doi = {10.1073/pnas.0610245104},
  eprint = {0610104},
  isbn = {0610245104},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {may},
  number = {18},
  pages = {7332--7336},
  pmid = {17456605},
  primaryclass = {physics},
  title = {{Structure and tie strengths in mobile communication networks}},
  url = {http://arxiv.org/abs/physics/0610104{\%}0Ahttp://dx.doi.org/10.1073/pnas.0610245104},
  volume = {104},
  year = {2006}
}
@article{Szabo2006,
  abstract = {While there is ample evidence that social and communication networks play a key role during the spread of new ideas, products, or services, network effects are expected to have diminished influence in the stationary state, when all users are aware of the innovation, and its usage pattern is determined mainly by its utility to the user. Here we study four mobile phone-based services available to over six million subscribers, allowing us to simultaneously monitor the communication network between individuals and the time-resolved service usage patterns. We find that usage highly correlates with the structure of the communication network, and demonstrate the coexistence on the same social network of two distinct usage classes, network effects being responsible for the quantifiable differences between them. To test the predictive power of our theory, we demonstrate that traditional marketing techniques are ineffective in permanently boosting service adoption, and propose a hub-based incentive mechanism that has the potential to enhance usage for one of the two service classes.},
  archiveprefix = {arXiv},
  arxivid = {physics/0611177},
  author = {Szabo, G and Barabasi, A L},
  eprint = {0611177},
  journal = {Arxiv preprint physics0611177},
  month = {nov},
  pages = {12},
  primaryclass = {physics},
  title = {{Network effects in service usage}},
  url = {http://arxiv.org/abs/physics/0611177},
  volume = {22},
  year = {2006}
}
@article{WoleOlatokun2006,
  abstract = {Purpose – The purpose of this study is to investigate the use of global system for mobile communications (GMS) at the University of Ibadan, Nigeria, emphasizing the nature and characteristics of the activities for which it is used, the factors that promote or beset its use, its benefits and the quality of services provided by the operators. Design/methodology/approach – The study adopted a descriptive survey design. A two-stage stratified sampling technique was adopted for selecting a sample of 456 staff and students of the University of Ibadan that form the target population. The questionnaire was the main data collection instrument while frequency and percentage distributions were the analytical tools adopted. Findings – Findings show a significant use of the GSM for social activities (getting in touch with friends and relations) while its use in research and academic activities was less significant. Also a number of inhibitors of effective GSM use in the University of Ibadan such as limited network coverage, unstable network and difficulty in making calls, etc. were identified. Originality/value – This study, apart from throwing light on the patterns of the use of GSM in the University of Ibadan, serves as a guide to policy makers to review the policy on telecommunications so as to allow for more and more competitors to engage in the telephony service. The study recommends that the government need to promote a competitive mobile phone market for more players to come into the sector and an upgrade in the communication standard for better GSM services in Nigeria. - See more at: http://0-www.emeraldinsight.com.library.ada.edu.az/journals.htm?issn=0264-0473{\&}volume=24{\&}issue=4{\&}articleid=1567629{\&}show=abstract{\#}sthash.Atykkpvy.dpuf},
  author = {Olatokun, Michael Wole and Bodunwa, Ibilola Oluseyi},
  doi = {10.1108/02640470610689214},
  isbn = {0264-0473, 0264-0473},
  issn = {02640473},
  journal = {Electronic Library},
  keywords = {Mobile communication systems,Nigeria,Telecommunications,Wireless},
  month = {jul},
  number = {4},
  pages = {530--547},
  title = {{GSM usage at the University of Ibadan}},
  url = {https://www.emeraldinsight.com/doi/10.1108/02640470610689214},
  volume = {24},
  year = {2006}
}
@article{Rose2006,
  abstract = {The provision of road-based travel-time information often relies on speed data collected from inductive loops imbedded in the pavement. While inductive loops are commonly installed on urban freeways, they are neither configured nor ideally located to provide speed data on arterial roads. Dissemination of dynamic, network-wide travel information to road users is, therefore, likely to require alternative data collection tech- niques. This review considers the state of practice in relation to using mobile phones as traffic probes, assesses the prospects for this data collection option and identifies unre- solved issues that may have implications for obtaining real-time traffic information using mobile phones as probes. The use of mobile phones as traffic probes is appealing because the necessary infrastructure is already in place in most urban areas. Traffic speed informa- tion can be obtained by passively monitoring data transmission in the mobile phone network. International experience provides encouraging signs about the potential of mobile phones as traffic probes. Issues still to be resolved include potential public concerns about privacy, growing awareness of the road safety implications of mobile phone use and the need to understand better the quality of the data obtained from mobile phone probes. Introduction},
  author = {Rose, Geoff},
  doi = {10.1080/01441640500361108},
  isbn = {01441647},
  issn = {01441647},
  journal = {Transport Reviews},
  month = {may},
  number = {3},
  pages = {275--291},
  pmid = {20063317},
  publisher = { Routledge },
  title = {{Mobile phones as traffic probes: Practices, prospects and issues}},
  url = {http://www.tandfonline.com/doi/abs/10.1080/01441640500361108},
  volume = {26},
  year = {2006}
}
@article{Bar-Gera2007,
  abstract = {The purpose of this paper is to examine the performance of a new operational system for measuring traffic speeds and travel times which is based on information from a cellular phone service provider. Cellular measurements are compared with those obtained by dual magnetic loop detectors. The comparison uses data for a busy 14 km freeway with 10 interchanges, in both directions, during January-March of 2005. The dataset contains 1 284 587 valid loop detector speed measurements and 440 331 valid measurements from the cellular system, each measurement referring to a 5 min interval. During one week in this period, 25 floating car measurements were conducted as additional comparison observations. The analyses include visual, graphical, and statistical techniques; focusing in particular on comparisons of speed patterns in the time-space domain. The main finding is that there is a good match between the two measurement methods, indicating that the cellular phone-based system can be useful for various practical applications such as advanced traveler information systems and evaluating system performance for modeling and planning. {\textcopyright} 2007 Elsevier Ltd. All rights reserved.},
  author = {Bar-Gera, Hillel},
  doi = {10.1016/j.trc.2007.06.003},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {Cellular phones,Probe vehicles,Travel time measurement},
  month = {dec},
  number = {6},
  pages = {380--391},
  pmid = {1080885},
  title = {{Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: A case study from Israel}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X07000393},
  volume = {15},
  year = {2007}
}
@article{Amin2007,
  abstract = {Purpose - Many banks consider mobile-based technologies have improved the banking services through introduction of new banking facilities. One of the latest facilities developed in this area is the "mobile credit card." The purpose of this study is to examine the factors that determine intention to use mobile credit card among Malaysia bank customers, as their new way in conducting payment transactions. Design/methodology/approach - The technology acceptance model (TAM) was used as the base model in order to develop the modified version of TAM to better reflect mobile credit card. In the modified model, perceived credibility and the amount of information on mobile credit card were added, in addition to perceived usefulness and perceived ease of use. Findings - Results suggest that perceived usefulness, perceived ease of use, perceived credibility and the amount of information on mobile credit cards are important determinants to predict Malaysia bank customers' intentions to use mobile credit card. Needless to say, the paper is exploratory in nature. Research limitations/implications - This study suffers from two limitations. The discussion of these limitations is provided in the last part of this paper. Practical implications - Useful to Islamic banking institutions planning further mobile credit card services for their customers. Originality/value - Extends the understanding of TAM to newly emerging context of mobile credit.},
  author = {Hanudin, Amin},
  doi = {10.1108/09685220710817789},
  isbn = {1355585101109},
  issn = {09685227},
  journal = {Information Management {\&} Computer Security},
  keywords = {Banking,Communication technologies,Credit cards,Islam,Malaysia},
  month = {aug},
  number = {4},
  pages = {260--269},
  pmid = {4679168},
  title = {{An analysis of mobile credit card usage intentions}},
  url = {http://www.emeraldinsight.com/doi/10.1108/09685220710817789},
  volume = {15},
  year = {2007}
}
@article{Andersen2007,
  abstract = {Purpose - The purpose of this paper is to present a study that compares ownership and usage of new media among young "tween" consumers in Denmark and Hong Kong. Further, it shows the ways of finding new interesting web sites. Design/methodology/approach - In 2004-2005 a survey was conducted in Denmark and Hong Kong of 434 fourth, fifth and sixth class students. Questionnaires were distributed in six elementary schools. Hypotheses about new media ownership and usage in the two societies are formulated based on the economic development and individualistic/collective cultural dimensions of the societies. Findings - Household ownership of new media, ownership of mobile phone and heavy use of the internet were found to be more prevalent among Danish tweens than among Hong Kong tweens. Danish tweens were more likely to use mobile phones and the internet for interpersonal communication and for enjoyment than Hong Kong tweens. Hong Kong tweens used the internet more for educational purposes than Danish tweens. The results seem to support that adoption and consumption of new media are motivated differently in cultures of individualism and collectivism, and consequently that the tween consumer segment is not as globally homogeneous as it is claimed to be. Research limitations/implications - The study was based on a convenience sample, thus it may be problematic to generalize from the findings. Practical implications - The study can serve as a guideline for marketing communication targeting tweens. The emphasis on the hedonic use and social function of new media may be suitable for a highly developed, individualistic society. In collective societies, marketers may need to put emphasis on the instrumental values of new media, such as improving academic performance. Originality/value - This paper offers insights into designing communication strategies for Danish and Hong Kong tweens, particularly when incorporating new media. Findings are compared with existing preconceptions of the tween segment in the marketing literature. {\textcopyright} Emerald Group Publishing Limited.},
  author = {Andersen, Lars P. and Tufte, Birgitte and Rasmussen, Jeanette and Chan, Kara},
  doi = {10.1108/07363760710822927},
  isbn = {0736-3761},
  issn = {07363761},
  journal = {Journal of Consumer Marketing},
  keywords = {Cross-cultural studies,Denmark,Hong Kong,Information media,Socialization,Youth},
  month = {sep},
  number = {6},
  pages = {340--350},
  title = {{Tweens and new media in Denmark and Hong Kong}},
  url = {https://www.emeraldinsight.com/doi/10.1108/07363760710822927},
  volume = {24},
  year = {2007}
}
@inproceedings{Lee2007,
  abstract = {Existing trajectory clustering algorithms group similar trajectories as a whole, thus discovering common trajectories. Our key observation is that clustering trajectories as a whole could miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, especially if we have regions of special interest for analysis. In this paper, we propose a new partition-and-group framework for clustering trajectories, which partitions a trajectory into a set of line segments, and then, groups similar line segments together into a cluster. The primary advantage of this framework is to discover common sub-trajectories from a trajectory database. Based on this partition-and-group framework, we develop a trajectory clustering algorithm TRACLUS. Our algorithm consists of two phases: partitioning and grouping. For the first phase, we present a formal trajectory partitioning algorithm using the minimum description length(MDL) principle. For the second phase, we present a density-based line-segment clustering algorithm. Experimental results demonstrate that TRACLUS correctly discovers common sub-trajectories from real trajectory data.},
  address = {New York, New York, USA},
  author = {Lee, Jae-Gil and Han, Jiawei and Whang, Kyu-Young},
  booktitle = {Proceedings of the 2007 ACM SIGMOD international conference on Management of data  - SIGMOD '07},
  doi = {10.1145/1247480.1247546},
  isbn = {9781595936868},
  issn = {07308078},
  pages = {593},
  publisher = {ACM Press},
  title = {{Trajectory clustering}},
  url = {http://portal.acm.org/citation.cfm?doid=1247480.1247546},
  year = {2007}
}
@article{Liao2007a,
  abstract = {This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through an urban community. The model uses multiple levels of abstraction in order to bridge the gap between raw GPS sensor measurements and high level information such as a user's destination and mode of transportation. To achieve efficient inference, we apply Rao-Blackwellized particle filters at multiple levels of the model hierarchy. Locations such as bus stops and parking lots, where the user frequently changes mode of transportation, are learned from GPS data logs without manual labeling of training data. We experimentally demonstrate how to accurately detect novel behavior or user errors (e.g. taking a wrong bus) by explicitly modeling activities in the context of the user's historical data. Finally, we discuss an application called "Opportunity Knocks" that employs our techniques to help cognitively-impaired people use public transportation safely. {\textcopyright} 2007 Elsevier B.V. All rights reserved.},
  author = {Liao, Lin and Patterson, Donald J. and Fox, Dieter and Kautz, Henry},
  doi = {10.1016/j.artint.2007.01.006},
  isbn = {0262511835},
  issn = {00043702},
  journal = {Artificial Intelligence},
  keywords = {Activity recognition,Hierarchical Markov model,Location tracking,Novelty detection,Rao-Blackwellized particle filters},
  month = {apr},
  number = {5-6},
  pages = {311--331},
  title = {{Learning and inferring transportation routines}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0004370207000380},
  volume = {171},
  year = {2007}
}
@book{Ieee,
  abstract = {Bibliographic Level Mode of Issuance: Monograph.},
  author = {Ieee and Ieee},
  isbn = {9781424470761},
  title = {{{\{}I{\}}nternational {\{}C{\}}onference on {\{}M{\}}obile {\{}D{\}}ata {\{}M{\}}anagement}},
  year = {2007}
}
@inproceedings{Zang2007,
  abstract = {Locating mobile users and devices efficiently is a critical operation in cellular networks. This is done using a combination of location update(by the mobile) and paging (by the network). The paging scheme determines how and where to search for a mobile user given the latestlocation update information from that user. In this paper, we considerhow to increase the efficiency of the paging scheme. Much previous work has relied on simulation or modeling to design and evaluate the performance of proposed paging schemes. We take a different, data-driven approach in how we design and evaluate our solution. Specifically, we mine more than 300 million call records from a large cellular operator to characterize user mobility and create mobility profiles. We then develop a family ofprofile-based paging techniques, considering both static schemes and dynamic schemes which adapt as user profiles continuously get updated. We find that our paging techniques can dramatically reducesignaling load (up to 80{\%}) with minimal increase in paging delay (usually less than 10{\%}).},
  address = {New York, New York, USA},
  author = {Zang, Hui and Bolot, Jean},
  booktitle = {Proceedings of the 13th annual ACM international conference on Mobile computing and networking  - MobiCom '07},
  doi = {10.1145/1287853.1287868},
  isbn = {9781595936813},
  pages = {123},
  publisher = {ACM Press},
  title = {{Mining call and mobility data to improve paging efficiency in cellular networks}},
  url = {http://portal.acm.org/citation.cfm?doid=1287853.1287868},
  year = {2007}
}
@article{Bettencourt2007,
  abstract = {We investigate the relationship between patenting activity and the population size of metropolitan areas in the United States over the last two decades (1980-2001). We find a clear superlinear effect, whereby new patents are granted disproportionately in larger urban centers, thus showing increasing returns in inventing activity with respect to population size. We characterize this relation quantitatively as a power law with an exponent larger than unity. This phenomenon is commensurate with the presence of larger numbers of inventors in larger metropolitan areas, which we find follows a quantitatively similar superlinear relationship to population, while the productivity of individual inventors stays essentially constant across metropolitan areas. We also find that structural measures of the patent co-authorship network although weakly correlated to increasing rates of patenting, are not enough to explain them. Finally, we show that R{\&}D establishments and employment in other creative professions also follow superlinear scaling relations to metropolitan population size, albeit possibly with different exponents. {\textcopyright} 2006 Elsevier B.V. All rights reserved.},
  author = {Bettencourt, Luis M.A. and Lobo, Jos{\'{e}} and Strumsky, Deborah},
  doi = {10.1016/j.respol.2006.09.026},
  isbn = {0048-7333},
  issn = {00487333},
  journal = {Research Policy},
  keywords = {Agglomeration,Network effects,Patenting,Scaling,Urban scale},
  month = {feb},
  number = {1},
  pages = {107--120},
  pmid = {17438298},
  title = {{Invention in the city: Increasing returns to patenting as a scaling function of metropolitan size}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0048733306001661},
  volume = {36},
  year = {2007}
}
@article{MohdSuki2007,
  abstract = {Mobile phone usage for m-learning: comparing heavy and light mobile phone users},
  author = {Suki, Norbayah Mohd and Suki, Norazah Mohd},
  doi = {10.1108/10650740710835779},
  isbn = {10650741},
  issn = {10650741},
  journal = {Campus-Wide Information Systems},
  keywords = {Learning,Malaysia,Mobile communications systems},
  month = {nov},
  number = {5},
  pages = {355--365},
  pmid = {218046377},
  title = {{Mobile phone usage for m-learning: Comparing heavy and light mobile phone users}},
  url = {http://www.emeraldinsight.com/doi/10.1108/10650740710835779},
  volume = {24},
  year = {2007}
}
@article{Munnukka2007,
  abstract = {Purpose - The purpose of this paper is to study consumers' adoption of mobile communications services, and to explore common denominators uniting those most likely to be early adopters; thereby, to help practitioners to predict early adoption and segment the market. Design/methodology/approach - Data were collected by postal questionnaire from 26 per cent of a sample of 3,000 customers of a telecommunications service provider in Finland, stratified into three sub-samples according to type of usage. For this paper, the returns from the two sub-samples with the highest rates of use were analysed. Findings - Previous experience of related types of communications services significantly and positively influenced adoption of new mobile services. Certain of the respondents' demographic characteristics were also closely associated with early adoption. Research limitations/implications - Further studies are required before the findings can be applied beyond Scandinavia. Qualitative research could enhance understanding of the roles of personal innovativeness and income, in particular, in adoption of mobile communications services. Practical implications - Mobile communications service providers in Scandinavia now have a tested basis for identification of early adopters, segmentation of the market, and targeting of marketing campaigns. Originality/value - The study tested theoretical constructs used widely in other fields, and identified adjustments required for transfer to the mobile communications service context.},
  author = {Munnukka, Juha},
  doi = {10.1108/02634500710834188},
  issn = {0263-4503},
  journal = {Marketing Intelligence {\&} Planning},
  month = {oct},
  number = {7},
  pages = {719--731},
  title = {{Characteristics of early adopters in mobile communications markets}},
  url = {http://www.emeraldinsight.com/doi/10.1108/02634500710834188},
  volume = {25},
  year = {2007}
}
@article{Liao2007,
  abstract = {Purpose - The purpose of this study is to analyse factors influencing subscribers' usage of 3G mobile services in Taiwan. Design/methodology/approach - The research model, based on a technology acceptance model (TAM) and added perceived enjoyment, was tested by means of a two-stage structure equation modelling approach. Data were collected from 532 respondents via a web questionnaire survey. Findings - The findings indicate that perceived usefulness, perceived ease of use and perceived enjoyment are positively related to attitude, and perceived enjoyment has a positive influence on perceived usefulness. Practical implications - The findings suggest users of 3G mobile services need to be provided with more diverse and entertaining ways of communicating, which are at the same time easily accessible and convenient to use. Originality/value - A new correlation from perceived enjoyment to perceived usefulness was found to have a significant effect. This finding indicates enjoyment as a key factor influences customers' adoption of 3G services. [ABSTRACT FROM AUTHOR]},
  archiveprefix = {arXiv},
  arxivid = {http://dx.doi.org/10.1108/BIJ-10-2012-0068},
  author = {Liao, Chun Hsiung and Tsou, Chun Wang and Huang, Ming Feng},
  doi = {10.1108/14684520710841757},
  eprint = {/dx.doi.org/10.1108/BIJ-10-2012-0068},
  isbn = {1468-4527},
  issn = {14684527},
  journal = {Online Information Review},
  keywords = {Mobile communication systems,Perception,Taiwan,User studies},
  month = {nov},
  number = {6},
  pages = {759--774},
  pmid = {42012058},
  primaryclass = {http:},
  title = {{Factors influencing the usage of 3G mobile services in Taiwan}},
  url = {http://www.emeraldinsight.com/doi/10.1108/14684520710841757},
  volume = {31},
  year = {2007}
}
@article{Gonzalez2008,
  abstract = {Despite their importance for urban planning, traffic forecasting and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited owing to the lack of tools to monitor the time-resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period. We find that, in contrast with the random trajectories predicted by the prevailing L{\{}{\'{e}}{\}}vy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time-independent characteristic travel distance and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent-based modelling.},
  archiveprefix = {arXiv},
  arxivid = {0806.1256},
  author = {Gonz{\'{a}}lez, Marta C. and Hidalgo, C{\'{e}}sar A. and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1038/nature06958},
  eprint = {0806.1256},
  isbn = {1476-4687 (Electronic)$\backslash$r0028-0836 (Linking)},
  issn = {14764687},
  journal = {Nature},
  keywords = {cdr,mobility},
  mendeley-tags = {cdr,mobility},
  month = {jun},
  number = {7196},
  pages = {779--782},
  pmid = {18528393},
  publisher = {Nature Publishing Group},
  title = {{Understanding individual human mobility patterns}},
  url = {http://www.nature.com/doifinder/10.1038/nature06958},
  volume = {453},
  year = {2008}
}
@article{Candia2008,
  abstract = {Novel aspects of human dynamics and social interactions are investigated by means of mobile phone data. Using extensive phone records resolved in both time and space, we study the mean collective behavior at large scales and focus on the occurrence of anomalous events. We discuss how these spatiotemporal anomalies can be described using standard percolation theory tools. We also investigate patterns of calling activity at the individual level and show that the interevent time of consecutive calls is heavy-tailed. This finding, which has implications for dynamics of spreading phenomena in social networks, agrees with results previously reported on other human activities.},
  archiveprefix = {arXiv},
  arxivid = {0710.2939},
  author = {Candia, Juli{\'{a}}n and Gonz{\'{a}}lez, Marta C. and Wang, Pu and Schoenharl, Timothy and Madey, Greg and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1088/1751-8113/41/22/224015},
  eprint = {0710.2939},
  isbn = {1751-8121},
  issn = {17518113},
  journal = {Journal of Physics A: Mathematical and Theoretical},
  month = {jun},
  number = {22},
  pages = {224015},
  title = {{Uncovering individual and collective human dynamics from mobile phone records}},
  url = {http://stacks.iop.org/1751-8121/41/i=22/a=224015?key=crossref.97d23b44de724a7398482cd45c7fe01a},
  volume = {41},
  year = {2008}
}
@article{Sims2008,
  abstract = {Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology. L{\'{e}}vy walks are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators-sharks, bony fishes, sea turtles and penguins-exhibit L{\'{e}}vy-walk-like behaviour close to a theoretical optimum. Prey density distributions also display L{\'{e}}vy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting L{\'{e}}vy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why L{\'{e}}vy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions.},
  archiveprefix = {arXiv},
  arxivid = {Figures, S., 2010. Supplementary information. Nature, 1(c), pp.1–7. Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3006164{\&}tool=pmcentrez{\&}rendertype=abstract.},
  author = {Sims, David W. and Southall, Emily J. and Humphries, Nicolas E. and Hays, Graeme C. and Bradshaw, Corey J.A. and Pitchford, Jonathan W. and James, Alex and Ahmed, Mohammed Z. and Brierley, Andrew S. and Hindell, Mark A. and Morritt, David and Musyl, Michael K. and Righton, David and Shepard, Emily L.C. and Wearmouth, Victoria J. and Wilson, Rory P. and Witt, Matthew J. and Metcalfe, Julian D.},
  doi = {10.1038/nature06518},
  eprint = {/www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3006164{\&}tool=pmcentrez{\&}rendertype=abstract.},
  isbn = {0028-0836},
  issn = {14764687},
  journal = {Nature},
  month = {feb},
  number = {7182},
  pages = {1098--1102},
  pmid = {18305542},
  primaryclass = {Figures, S., 2010. Supplementary information. Nature, 1(c), pp.1–7. Available at: http:},
  title = {{Scaling laws of marine predator search behaviour}},
  url = {http://www.nature.com/articles/nature06518},
  volume = {451},
  year = {2008}
}
@inproceedings{Agrawal2008,
  abstract = {Pattern matching over event streams is increasingly being employed in many areas including financial services, RFID- based inventory management, click stream analysis, and elec- tronic health systems. While regular expression matching is well studied, pattern matching over streams presents two new challenges: Languages for pattern matching over streams are significantly richer than languages for regular expression matching. Furthermore, efficient evaluation of these pattern queries over streams requires new algorithms and optimiza- tions: the conventional wisdom for stream query processing (i.e., using selection-join-aggregation) is inadequate. In this paper, we present a formal evaluation model that offers precise semantics for this new class of queries and a query evaluation framework permitting optimizations in a principled way. We further analyze the runtime complex- ity of query evaluation using this model and develop a suite of techniques that improve runtime efficiency by exploiting sharing in storage and processing. Our experimental results provide insights into the various factors on runtime perfor- mance and demonstrate the significant performance gains of our sharing techniques.},
  address = {New York, New York, USA},
  author = {Agrawal, Jagrati and Diao, Yanlei and Gyllstrom, Daniel and Immerman, Neil},
  booktitle = {Proceedings of the 2008 ACM SIGMOD international conference on Management of data  - SIGMOD '08},
  doi = {10.1145/1376616.1376634},
  isbn = {9781605581026},
  issn = {07308078},
  pages = {147},
  publisher = {ACM Press},
  title = {{Efficient pattern matching over event streams}},
  url = {http://portal.acm.org/citation.cfm?doid=1376616.1376634},
  year = {2008}
}
@inproceedings{Seshadri2008,
  abstract = {We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distributions of the number of phone calls per customer; the total talk minutes per customer; and the distinct num- ber of calling partners per customer. We find that these distributions are skewed, and that they significantly deviate from what would be expected by power-law and lognormal distributions. To analyze our observed distributions (of number of calls, distinct call partners, and total talk time), we propose Pow- erTrack , a method which fits a lesser known but more suitable distribution, namely the Double Pareto LogNormal (DPLN) distribution, to our data and track its parameters over time. Using PowerTrack , we find that our graph changes over time in a way consistent with a generative pro- cess that naturally results in the DPLN distributions we observe. Furthermore, we show that this generative process lends itself to a natural and appealing social wealth inter- pretation in the context of social networks such as ours. We discuss the application of those results to our model and to forecasting.},
  address = {New York, New York, USA},
  author = {Seshadri, Mukund and Machiraju, Sridhar and Sridharan, Ashwin and Bolot, Jean and Faloutsos, Christos and Leskove, Jure},
  booktitle = {Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08},
  doi = {10.1145/1401890.1401963},
  isbn = {9781605581934},
  pages = {596},
  publisher = {ACM Press},
  title = {{Mobile call graphs}},
  url = {http://dl.acm.org/citation.cfm?doid=1401890.1401963},
  year = {2008}
}
@inproceedings{Dasgupta2008,
  abstract = {Social Network Analysis has emerged as a key paradigm in modern sociology, technology, and information sciences. The paradigm stems from the view that the attributes of an individual in a network are less important than their ties (relationships) with other individuals in the network. Exploring the nature and strength of these ties can help understand the structure and dynamics of social networks and explain real-world phenomena, ranging from organizational efficiency to the spread of information and disease. In this paper, we examine the communication patterns of millions of mobile phone users, allowing us to study the underlying social network in a large-scale communication network. Our primary goal is to address the role of social ties in the formation and growth of groups, or communities, in a mobile network. In particular, we study the evolution of churners in an operator's network spanning over a period of four months. Our analysis explores the propensity of a subscriber to churn out of a service provider's network depending on the number of ties (friends) that have already churned. Based on our findings, we propose a spreading activation-based technique that predicts potential churners by examining the current set of churners and their underlying social network. The efficiency of the prediction is expressed as a lift curve, which indicates the fraction of all churners that can be caught when a certain fraction of subscribers were contacted.},
  address = {New York, New York, USA},
  author = {Dasgupta, Koustuv and Singh, Rahul and Viswanathan, Balaji and Chakraborty, Dipanjan and Mukherjea, Sougata and Nanavati, Amit A and Joshi, Anupam},
  booktitle = {Edbt},
  doi = {10.1145/1353343.1353424},
  isbn = {9781595939265},
  pages = {1--10},
  publisher = {ACM Press},
  title = {{Social Ties and their Relevance to Churn in Mobile Telecom Networks}},
  url = {http://portal.acm.org/citation.cfm?doid=1352431.1352512},
  year = {2008}
}
@article{Hargittai2008,
  abstract = {This paper looks at the prevalence of creative activity and sharing in an age when the barriers to disseminating material have been considerably lowered compared with earlier times. The authors use unique data to explore the extent to which young adults create video, music, writing and artistic photography, as well as the prevalence of sharing such material online. Findings suggest that despite new opportunities to engage in such distribution of content, relatively few people are taking advantage of these recent developments. Moreover, neither cre- ation nor sharing is randomly distributed among a diverse group of young adults. Consistent with existing literature, creative activity is related to a person's socioeconomic status as measured by parental schooling. The novel act of sharing online, however, is considerably different by gender with men much more likely to engage in it. However, once internet user skill is controlled for, men and women are equally likely to post their materials on the Web.},
  author = {Hargittai, Eszter and Walejko, Gina},
  doi = {10.1080/13691180801946150},
  isbn = {1369-118X},
  issn = {1369118X},
  journal = {Information Communication and Society},
  keywords = {Arts,Content,Creativity,Digital divide,Digital inequality,Digital literacy,Gender,Inequality,Internet,Music,Participation,Posting,Sharing,Skill,Users,Video,Web},
  number = {2},
  pages = {239--256},
  title = {{The participation divide: Content creation and sharing in the digital age}},
  volume = {11},
  year = {2008}
}
@article{Eagle2009,
  abstract = {Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95{\%} of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1408.1149},
  author = {Eagle, N. and Pentland, A. and Lazer, D.},
  doi = {10.1073/pnas.0900282106},
  eprint = {arXiv:1408.1149},
  isbn = {1091-6490 (Electronic)$\backslash$r0027-8424 (Linking)},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {sep},
  number = {36},
  pages = {15274--15278},
  pmid = {19706491},
  title = {{Inferring friendship network structure by using mobile phone data}},
  url = {http://www.pnas.org/cgi/doi/10.1073/pnas.0900282106},
  volume = {106},
  year = {2009}
}
@incollection{Batty2009,
  abstract = {Glossary Definition of the Subject Introduction Cities in Equilibrium Urban Dynamics Comprehensive System Models of Urban Structure Future Directions Bibliography},
  address = {New York, NY},
  archiveprefix = {arXiv},
  arxivid = {0706.0024},
  author = {Batty, Michael},
  booktitle = {Encyclopedia of Complexity and Systems Science},
  doi = {10.1007/978-0-387-30440-3_69},
  eprint = {0706.0024},
  isbn = {978-0-387-75888-6, 978-0-387-30440-3},
  issn = {1467-1298},
  pages = {1041--1071},
  pmid = {18764023},
  publisher = {Springer New York},
  title = {{Cities as Complex Systems: Scaling, Interaction, Networks, Dynamics and Urban Morphologies}},
  url = {http://link.springer.com/10.1007/978-0-387-30440-3{\_}69},
  year = {2009}
}
@inproceedings{Belwal2009,
  abstract = {The purpose of this paper is to study the mobile phone usage behavior of$\backslash$nuniversity students in Oman. A survey was conducted in Muscat and Sohar$\backslash$ncities of Oman where 200 students were contacted using questionnaires$\backslash$nand interview methods. Students in higher educational institutions were$\backslash$ncovered and hypotheses about mobile services usage among students were$\backslash$nformulated and tested on different aspects of mobile phone use. It was$\backslash$nrealized that Oman is very close to secure 100{\%} penetration in mobile$\backslash$nadoption and newer mobile technologies are available. Mobile usage$\backslash$nrelated statistics revealed that a majority of students prefer to have$\backslash$nprepaid connections, spend more than 10 Omani Rials per month on$\backslash$nservices, make less than 10 calls but more than 10 SMS per day, and$\backslash$ndepend on their parents for payment of bills. Nokia is the most popular$\backslash$nhandset brand among students and they tend to change handsets at least$\backslash$nin a year. It was significantly tested true that students have higher$\backslash$naffinity to buy top end mobile phones, they feel uncomfortable without$\backslash$nmobile phones, they keep their mobile phone switched on 24 hours, and$\backslash$nthey are equipped with almost every feature in their mobile.},
  author = {Beiwal, Rakesh and Beiwal, Shweta},
  booktitle = {Proceedings - 2009 International Conference on New Trends in Information and Service Science, NISS 2009},
  doi = {10.1109/NISS.2009.65},
  isbn = {9780769536873},
  month = {jun},
  pages = {954--962},
  publisher = {IEEE},
  title = {{Mobile phone usage behavior of university students in oman}},
  url = {http://ieeexplore.ieee.org/document/5260738/},
  year = {2009}
}
@inproceedings{Annafari2009,
  abstract = {This paper advances a new concept, quasi-subscribers, to define the$\backslash$nincidence of mobile phone multiple subscriptions. Through survey data,$\backslash$nthe paper shows that in Sweden the number of quasi-subscribers$\backslash$nconstitutes a significant portion of the mobile phone subscribers.$\backslash$nHence, there is a significant bias in the traditional method of$\backslash$nmeasuring mobile subscribers which is mostly based on the number of$\backslash$nsubscriptions and active SIM cards in the population. This situation is$\backslash$nlikely to hold for many other countries. Such a bias may contribute to$\backslash$nfaulty policy, strategic and research analysis, with possibly$\backslash$nunfavorable consequences for decision-making that is based on such$\backslash$nanalysis.},
  author = {Annafari, Mohammad Tsani and Bohlin, Erik},
  booktitle = {2009 Global Information Infrastructure Symposium, GIIS '09},
  doi = {10.1109/GIIS.2009.5307104},
  isbn = {9781424446247},
  keywords = {Estimation,Mobile phone,Non-subscribers,Quasi-subscribers},
  month = {jun},
  pages = {1--6},
  publisher = {IEEE},
  title = {{Estimating mobile phone non-subscribers and quasi-subscribers by sampling}},
  url = {http://ieeexplore.ieee.org/document/5307104/},
  year = {2009}
}
@book{Awan2009,
  abstract = {"IEEE Computer Society Order Number P3639"--Title page verso.},
  author = {Awan, Irfan. and {IEEE Computer Society.} and {University of Bradford.} and {Engineering and Physical Sciences Research Council.} and {Centre for Creative {\&} Cultural Knowledge Exchange.}},
  isbn = {9780769536392},
  pages = {1194},
  publisher = {IEEE Computer Society},
  title = {{Proceedings, the IEEE 23rd International Conference on Advanced Information Networking and Applications Workshops/Symposia : Bradford, United Kingdom : 26-29 May, 2009}},
  year = {2009}
}
@book{Awan2009a,
  abstract = {"IEEE Computer Society Order Number P3639"--Title page verso.},
  author = {Awan, Irfan. and {IEEE Computer Society.} and {University of Bradford.} and {Engineering and Physical Sciences Research Council.} and {Centre for Creative {\&} Cultural Knowledge Exchange.}},
  isbn = {9780769536392},
  pages = {1194},
  publisher = {IEEE Computer Society},
  title = {{Proceedings, the IEEE 23rd International Conference on Advanced Information Networking and Applications Workshops/Symposia : Bradford, United Kingdom : 26-29 May, 2009}},
  year = {2009}
}
@inproceedings{Teshirogi2009,
  abstract = {The earthquake with the seismic center around the coast of Miyagi prefecture and the oceanic trench of southern Sanriku is expected to occur with high probability. Enforcement of comprehensive anti-tsunami measures is expected with high emergency in the Sanriku region across Miyagi and Iwate prefecture. Consequently, a system is required that prefectures, cities, towns and villages collect swiftly and accurately the tsunami monitoring information that is necessary for evacuation behavior, relief and recovery activities, and deliver and share to the local residents. Regarding the disaster information service "Area Mail" that NTT DoCoMo started newly, it is possible to deliver information simultaneously for afflicted limited areas unlike traditional mobile e-mail system. It is thought that the Area Mail can be used to notify not only to inhabitants but also to the tourists (including foreigners) at the time of the disaster. Furthermore, because Area Mail covers the main fishery region in the coast, service to fishery workers is possible while they operate along the coast. They can avoid tsunami damage even in very early stages of an event. In this study, some issues of applying the Area Mail to tsunami warning for fishery workers are extracted. And a prototype is built to assess the feasibility.},
  author = {Teshirogi, Yasuaki and Sawamoto, Jun and Segawa, Norihisa and Sugino, Eiji},
  booktitle = {Proceedings - International Conference on Advanced Information Networking and Applications, AINA},
  doi = {10.1109/WAINA.2009.75},
  isbn = {9780769536392},
  issn = {1550445X},
  keywords = {Area mail,Component,Early warning system,Mobile phone,Tsunami disaster},
  month = {may},
  pages = {890--895},
  publisher = {IEEE},
  title = {{A proposal of tsunami warning system using area mail disaster information service on mobile phones}},
  url = {http://ieeexplore.ieee.org/document/5136763/},
  year = {2009}
}
@inproceedings{Vieira2009,
  abstract = {With the recent advancements and wide usage of location de- tection devices, large quantities of data are collected by GPS and cellular technologies in the form of trajectories. While most previous work on trajectory-based queries has concen- trated on traditional range, nearest-neighbor and similarity queries, there is an increasing interest in queries that capture the“aggregate”behavior of trajectories as groups. Consider, for example, finding groups of moving objects thatmove“to- gether”, i.e. within a predefined distance to each other, for a certain continuous period of time. Such queries typically arise in surveillance applications, e.g. identify groups of sus- picious people, convoys of vehicles, flocks of animals, etc. In this paper we first show that the on-line flock discov- ery problem is polynomial and then propose a framework and several strategies to discover such patterns in streaming spatio-temporal data. Experiments with real and synthetic trajectorial datasets show that the proposed algorithms are efficient and scalable.},
  address = {New York, New York, USA},
  author = {Vieira, Marcos R. and Bakalov, Petko and Tsotras, Vassilis J.},
  booktitle = {Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '09},
  doi = {10.1145/1653771.1653812},
  isbn = {9781605586496},
  pages = {286},
  publisher = {ACM Press},
  title = {{On-line discovery of flock patterns in spatio-temporal data}},
  url = {http://portal.acm.org/citation.cfm?doid=1653771.1653812},
  year = {2009}
}
@inproceedings{Crandall2009,
  abstract = {We investigate how to organize a large collection of geotagged photos, working with a dataset of about 35 million images collected from Flickr. Our approach combines content analysis based on text tags and image data with structural analysis based on geospatial data. We use the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places. We then study the interplay between this structure and the content, using classification methods for predicting such locations from visual, textual and temporal features of the photos. We find that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features. We illustrate using these techniques to organize a large photo collection, while also revealing various interesting properties about popular cities and landmarks at a global scale.},
  address = {New York, New York, USA},
  author = {Crandall, David J. and Backstrom, Lars and Huttenlocher, Daniel and Kleinberg, Jon},
  booktitle = {Proceedings of the 18th international conference on World wide web - WWW '09},
  doi = {10.1145/1526709.1526812},
  isbn = {9781605584874},
  issn = {08963207},
  pages = {761},
  publisher = {ACM Press},
  title = {{Mapping the world's photos}},
  url = {http://portal.acm.org/citation.cfm?doid=1526709.1526812},
  year = {2009}
}
@inproceedings{Trestian2009,
  address = {New York, New York, USA},
  author = {Trestian, Ionut and Ranjan, Supranamaya and Kuzmanovic, Aleksandar and Nucci, Antonio},
  booktitle = {Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference - IMC '09},
  doi = {10.1145/1644893.1644926},
  isbn = {9781605587714},
  keywords = {application interest,cellular network,hotspot,human mobility,location based services,mobile network,serendipity},
  pages = {267},
  publisher = {ACM Press},
  title = {{Measuring serendipity}},
  url = {http://portal.acm.org/citation.cfm?doid=1644893.1644926},
  year = {2009}
}
@book{IEEEComputerSociety.TechnicalCommitteeonScalableComputing.2009,
  author = {{IEEE Computer Society. Technical Committee on Scalable Computing.} and {IEEE Computer Society.} and {Institute of Electrical and Electronics Engineers.} and {St. Francis Xavier University.} and {IEEE International Conference on Social Computing.} and {IEEE International Conference on Privacy}, Security and {EUC 2009 (2009 : Vancouver}, B.C.)},
  isbn = {9781424453344},
  publisher = {IEEE Computer Society},
  title = {{Proceedings : 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 : 7th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2009 : 2009 IEEE International Conference on Privacy, Security, Risk, an}},
  year = {2009}
}
@inproceedings{Eagle2009b,
  abstract = {We present a comparative analysis of the behavioral dynamics of rural and urban societies using four years of mobile phone data from all 1.4M subscribers within a small country. We use information from communication logs and top up denominations to characterize attributes such as socioeconomic status and region. We show that rural and urban communities differ dramatically not only in terms of personal network topologies, but also in terms of inferred behavioral characteristics such as travel. We confirm the hypothesis for behavioral adaptation, demonstrating that individuals change their patterns of communication to increase the similarity with their new social environment. To our knowledge, this is the first comprehensive comparison between regional groups of this size.},
  author = {Eagle, Nathan and {De Montjoye}, Yves Alexandre and Bettencourt, Luis M A},
  booktitle = {Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009},
  doi = {10.1109/CSE.2009.91},
  isbn = {9780769538235},
  pages = {144--150},
  publisher = {IEEE},
  title = {{Community computing: Comparisons between rural and urban societies using mobile phone data}},
  url = {http://ieeexplore.ieee.org/document/5284288/},
  volume = {4},
  year = {2009}
}
@book{InstituteofElectricalandElectronicsEngineers.2009,
  abstract = {Recently the companiespsila interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. In the last few years, several projects have been carried out, with the aim of the development of innovative systems capable of collecting and sharing information. This paper proposes a knowledge management system, whose main feature is an ontological knowledge representation. The ontological representation of data allows of specializing the reasoning capabilities and of providing ad hoc behaviors. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a document management system and an expert system to share documents and to plan how-to best use firmspsila knowledge.},
  author = {Ribino, Patrizia and Oliveri, Antonio and Re, Giuseppe Lo and Gaglio, Salvatore},
  booktitle = {2009 International Conference on New Trends in Information and Service Science},
  doi = {10.1109/NISS.2009.105},
  isbn = {978-0-7695-3687-3},
  pages = {1025--1033},
  publisher = {IEEE Computer Society},
  title = {{A Knowledge Management System Based on Ontologies}},
  url = {http://ieeexplore.ieee.org/document/5260686/},
  year = {2009}
}
@article{Lazer2009,
  abstract = {Web of Science},
  author = {Lazer, David and Pentland, Alex and Adamic, Lada and Aral, Sinan and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}} and Brewer, Devon and Christakis, Nicholas and Contractor, Noshir and Fowler, James and Gutmann, Myron and Jebara, Tony and King, Gary and Macy, Michael and Roy, Deb and {Van Alstyne}, Marshall},
  doi = {10.1126/science.1167742},
  isbn = {1939-0068},
  issn = {00368075},
  journal = {Science},
  month = {feb},
  number = {5915},
  pages = {721--723},
  pmid = {19197046},
  publisher = {NIH Public Access},
  title = {{Social science: Computational social science}},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/19197046 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2745217},
  volume = {323},
  year = {2009}
}
@article{Balcan2009,
  abstract = {Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. In order to study the interplay between small-scale commuting flows and long-range airline traffic in shaping the spatio-temporal pattern of a global epidemic we i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms; ii) integrate in a worldwide structured metapopulation epidemic model a time-scale separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short range mobility increases however the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multi-scale framework.},
  archiveprefix = {arXiv},
  arxivid = {0907.3304},
  author = {Balcan, Duygu and Colizza, Vittoria and Goncalves, Bruno and Hu, Hao and Ramasco, Jose J. and Vespignani, Alessandro},
  doi = {10.1073/pnas.0906910106},
  eprint = {0907.3304},
  isbn = {1091-6490},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {dec},
  number = {51},
  pages = {21484--21489},
  pmid = {20018697},
  title = {{Multiscale mobility networks and the large scale spreading of infectious diseases}},
  url = {http://arxiv.org/abs/0907.3304{\%}0Ahttp://dx.doi.org/10.1073/pnas.0906910106},
  volume = {106},
  year = {2009}
}
@article{Kovanen2010,
  abstract = {We present a study of the reciprocity of human behaviour based on mobile phone usage records. The underlying question is whether human relationships are mutual, in the sense that both are equally active in keeping up the relationship, or is it on the contrary typical that relationships are lopsided, with one party being significantly more active than the other. We study this question with the help of a mobile phone data set consisting of all mobile phone calls between 5.3 million customers of a single mobile phone operator. It turns out that lopsided relations are indeed quite common, to the extent that the variation cannot be explained by simple random deviations or by variations in personal activity. We also show that there is no non-trivial correlation between reciprocity and local network density.},
  archiveprefix = {arXiv},
  arxivid = {1002.0763},
  author = {Kovanen, Lauri and Saramaki, Jari and Kaski, Kimmo},
  eprint = {1002.0763},
  file = {::},
  month = {feb},
  title = {{Reciprocity of mobile phone calls}},
  url = {http://arxiv.org/abs/1002.0763},
  year = {2010}
}
@article{Herrera2010,
  abstract = {The growing need of the driving public for accurate traffic information has spurred the deployment of large scale dedicated monitoring infrastructure systems, which mainly consist in the use of inductive loop detectors and video cameras. On-board electronic devices have been proposed as an alternative traffic sensing infrastructure, as they usually provide a cost-effective way to collect traffic data, leveraging existing communication infrastructure such as the cellular phone network. A traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network. This article presents a field experiment nicknamed Mobile Century, which was conceived as a proof of concept of such a system. Mobile Century included 100 vehicles carrying a GPS-enabled Nokia N95 phone driving loops on a 10-mile stretch of I-880 near Union City, California, for 8. h. Data were collected using virtual trip lines, which are geographical markers stored in the handset that probabilistically trigger position and speed updates when the handset crosses them. The proposed prototype system provided sufficient data for traffic monitoring purposes while managing the privacy of participants. The data obtained in the experiment were processed in real-time and successfully broadcast on the internet, demonstrating the feasibility of the proposed system for real-time traffic monitoring. Results suggest that a 2-3{\%} penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow. Data presented in this article can be downloaded from http://traffic.berkeley.edu. {\textcopyright} 2009 Elsevier Ltd.},
  author = {Herrera, Juan C. and Work, Daniel B. and Herring, Ryan and Ban, Xuegang (Jeff) and Jacobson, Quinn and Bayen, Alexandre M.},
  doi = {10.1016/j.trc.2009.10.006},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {GPS-enabled cell phones,Mobile sensors,Traffic monitoring systems,Traffic sensors},
  month = {aug},
  number = {4},
  pages = {568--583},
  title = {{Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X09001430},
  volume = {18},
  year = {2010}
}
@article{Treiber2010,
  abstract = {Despite the availability of large empirical data sets and the long history of traffic modeling, the theory of traffic congestion on freeways is still highly controversial. In this contribution, we compare Kerner's three-phase traffic theory with the phase diagram approach for traffic models with a fundamental diagram. We discuss the inconsistent use of the term " traffic phase" and show that patterns demanded by three-phase traffic theory can be reproduced with simple two-phase models, if the model parameters are suitably specified and factors characteristic for real traffic flows are considered, such as effects of noise or heterogeneity or the actual freeway design (e.g. combinations of off- and on-ramps). Conversely, we demonstrate that models created to reproduce three-phase traffic theory create similar spatiotemporal traffic states and associated phase diagrams, no matter whether the parameters imply a fundamental diagram in equilibrium or non-unique flow- density relationships. In conclusion, there are different ways of reproducing the empirical stylized facts of spatiotemporal congestion patterns summarized in this contribution, and it appears possible to overcome the controversy by a more precise definition of the scientific terms and a more careful comparison of models and data, considering effects of the measurement process and the right level of detail in the traffic model used. {\textcopyright} 2010 Elsevier Ltd.},
  archiveprefix = {arXiv},
  arxivid = {1004.5545},
  author = {Treiber, Martin and Kesting, Arne and Helbing, Dirk},
  doi = {10.1016/j.trb.2010.03.004},
  eprint = {1004.5545},
  isbn = {0191-2615},
  issn = {01912615},
  journal = {Transportation Research Part B: Methodological},
  keywords = {Car-following models,Phase diagram,Pinch effect,Second-order traffic models,Synchronized traffic,Three-phase theory},
  month = {sep},
  number = {8-9},
  pages = {983--1000},
  title = {{Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S019126151000041X},
  volume = {44},
  year = {2010}
}
@book{Holma2010,
  abstract = {Now in its fifth edition, the bestselling book on UMTS has been updated to cover 3GPP WCDMA and High Speed Packet Access (HSPA) from Release 99 to Release 9. Written by leading experts in the field, the book explains HSPA performance based on simulations and field experience, and illustrates the benefits of HSPA evolution (HSPA+) both from the operators and from the end user?s perspective. It continues to provide updated descriptions of the 3GPP standard including the physical layer, radio protocols on layers 1-3 and a system architecture description. The challenges and solutions regarding terminal RF design are also discussed, including the benefits of HSPA+ power saving features. There is also the addition of a new chapter on femto cells as part of the updates to this fifth edition.Key updates include:HSPA evolution (HSPA+); Multicarrier HSPA solutions; HSPA femto cells (home base stations); TD-SCDMA system description; Terminal power consumption optimization. Updated description of LTE},
  address = {Chichester, UK},
  author = {Holma, Harri and Toskala, Antti},
  booktitle = {WCDMA for UMTS: HSPA Evolution and LTE: Fifth Edition},
  doi = {10.1002/9780470669501},
  editor = {Holma, Harri and Toskala, Antti},
  isbn = {9780470669501},
  month = {aug},
  pages = {1--597},
  publisher = {John Wiley {\&} Sons, Ltd},
  title = {{WCDMA for UMTS: HSPA Evolution and LTE: Fifth Edition}},
  url = {http://doi.wiley.com/10.1002/9780470669501},
  year = {2010}
}
@article{Song2010,
  abstract = {A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93{\%} potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.},
  archiveprefix = {arXiv},
  arxivid = {cond-mat/0307014},
  author = {Song, Chaoming and Qu, Zehui and Blumm, Nicholas and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1126/science.1177170},
  eprint = {0307014},
  isbn = {00368075},
  issn = {00368075},
  journal = {Science},
  month = {feb},
  number = {5968},
  pages = {1018--1021},
  pmid = {20167789},
  primaryclass = {cond-mat},
  title = {{Limits of predictability in human mobility}},
  url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1177170},
  volume = {327},
  year = {2010}
}
@article{Herrera2010a,
  abstract = {The growing need of the driving public for accurate traffic information has spurred the deployment of large scale dedicated monitoring infrastructure systems, which mainly consist in the use of inductive loop detectors and video cameras. On-board electronic devices have been proposed as an alternative traffic sensing infrastructure, as they usually provide a cost-effective way to collect traffic data, leveraging existing communication infrastructure such as the cellular phone network. A traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network. This article presents a field experiment nicknamed Mobile Century, which was conceived as a proof of concept of such a system. Mobile Century included 100 vehicles carrying a GPS-enabled Nokia N95 phone driving loops on a 10-mile stretch of I-880 near Union City, California, for 8. h. Data were collected using virtual trip lines, which are geographical markers stored in the handset that probabilistically trigger position and speed updates when the handset crosses them. The proposed prototype system provided sufficient data for traffic monitoring purposes while managing the privacy of participants. The data obtained in the experiment were processed in real-time and successfully broadcast on the internet, demonstrating the feasibility of the proposed system for real-time traffic monitoring. Results suggest that a 2-3{\%} penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow. Data presented in this article can be downloaded from http://traffic.berkeley.edu. {\textcopyright} 2009 Elsevier Ltd.},
  author = {Herrera, Juan C. and Work, Daniel B. and Herring, Ryan and Ban, Xuegang (Jeff) and Jacobson, Quinn and Bayen, Alexandre M.},
  doi = {10.1016/j.trc.2009.10.006},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {GPS-enabled cell phones,Mobile sensors,Traffic monitoring systems,Traffic sensors},
  month = {aug},
  number = {4},
  pages = {568--583},
  title = {{Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X09001430},
  volume = {18},
  year = {2010}
}
@incollection{Phithakkitnukoon2010,
  abstract = {Being able to understand dynamics of human mobility is essential for urban planning and transportation management. Besides geographic space, in this paper, we characterize mobility in a profile-based space (activity-aware map) that describes most probable activity associated with a specific area of space. This, in turn, allows us to capture the individual daily activity pattern and analyze the correlations among different people's work area's profile. Based on a large mobile phone data of nearly one million records of the users in the central Metro-Boston area, we find a strong correlation in daily activity patterns within the group of people who share a common work area's profile. In addition, within the group itself, the similarity in activity patterns decreases as their work places become apart.},
  archiveprefix = {arXiv},
  arxivid = {9780201398298},
  author = {Phithakkitnukoon, Santi and Horanont, Teerayut and {Di Lorenzo}, Giusy and Shibasaki, Ryosuke and Ratti, Carlo},
  booktitle = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-642-14715-9_3},
  eprint = {9780201398298},
  isbn = {3642147143},
  issn = {03029743},
  pages = {14--25},
  pmid = {20167789},
  title = {{Activity-aware map: Identifying human daily activity pattern using mobile phone data}},
  publisher = {Springer},
  url = {http://link.springer.com/10.1007/978-3-642-14715-9{\_}3},
  volume = {6219 LNCS},
  year = {2010}
}
@article{Cervero2010,
  abstract = {Concerns over rising fuel prices and greenhouse-gas emissions have prompted research into the influences of built environments on travel, notably vehicle miles traveled (VMT). On the basis of data from 370 US urbanized areas and using structural equation modeling, population densities are shown to be strongly and positively associated with VMT per capita (direct effect elasticity = -0.604); however, this effect is moderated by the traffic-inducing effects of denser urban settings having denser road networks and better local-retail accessibility (indirect effect elasticity = 0.223, yielding a net effect elasticity = -0.381). Accessibility to basic employment has comparatively modest effects, as do size of urbanized area, and rail-transit supplies and usage. Nevertheless, urban planning and city design should be part of any strategic effort to shrink the environmental footprint of the urban transportation sector.},
  author = {Cervero, Robert and Murakami, Jin},
  doi = {10.1068/a4236},
  isbn = {0308-518X},
  issn = {0308518X},
  journal = {Environment and Planning A},
  month = {feb},
  number = {2},
  pages = {400--418},
  title = {{Effects of built environments on vehicle miles traveled: Evidence from 370 US urbanized areas}},
  url = {http://journals.sagepub.com/doi/10.1068/a4236},
  volume = {42},
  year = {2010}
}
@article{Hao2010,
  abstract = {Microsimulation is becoming more popular in transportation research.$\backslash$nThis research explores the potential of microsimulation by integrating$\backslash$nan existing activity-based travel demand model, TASHA, with a dynamic$\backslash$nagent-based traffic simulation model, MATSim. Differences in model$\backslash$nprecisions from the two models are resolved through a series of data$\backslash$nconversions, and the models are able to form an iterative process$\backslash$nsimilar to previous modeling frameworks using TASHA and static assignment$\backslash$nusing Emme/2. The resulting model is then used for light-duty vehicle$\backslash$nemission modeling where the traditional average-speed modeling approach$\backslash$nis improved by exploiting agent-based traffic simulation results.$\backslash$nThis improved method of emission modeling is more sensitive to the$\backslash$neffect of congestion, and the linkage between individual vehicles$\backslash$nand link emissions is preserved. The results have demonstrated the$\backslash$nadvantages of the microsimulation approach over conventional methodologies$\backslash$nthat rely heavily on temporal or spatial aggregation. The framework$\backslash$ncan be improved by further enhancing the sensitivity of TASHA to$\backslash$ntravel time.},
  author = {Hao, Jiang and Hatzopoulou, Marianne and Miller, Eric},
  doi = {10.3141/2176-01},
  isbn = {0361-1981},
  issn = {0361-1981},
  journal = {Transportation Research Record: Journal of the Transportation Research Board},
  month = {jan},
  number = {1},
  pages = {1--13},
  pmid = {906},
  title = {{Integrating an Activity-Based Travel Demand Model with Dynamic Traffic Assignment and Emission Models}},
  url = {http://trrjournalonline.trb.org/doi/10.3141/2176-01},
  volume = {2176},
  year = {2010}
}
@article{Bradley2010,
  abstract = {This paper presents the regional travel forecasting model system (SACSIM) being used by the Sacramento (California) Area Council of Governments (SACOG). Within SACSIM an integrated activity-based disaggregate econometric model (DaySim) simulates each resident's full-day activity and travel schedule. Sensitivity to neighborhood scale is enhanced through disaggregation of the modeled outcomes in three key dimensions: purpose, time, and space. Each activity episode is associated with one of seven specific purposes, and with a particular parcel location at which it occurs. The beginning and ending times of all activity and travel episodes are identified within a specific 30-minute time period. Within SACSIM, DaySim equilibrates iteratively with traditional traffic assignment models. SACSIM was calibrated and tested for a base year of 2000 and for forecasts to the years 2005 and 2035, and was subjected to a formal peer-review. It was used to provide forecasts for the Regional Transportation Plan (RTP) and continues to be used for various policy analyses. The paper explains the model system structure and components, the integration with the traffic assignment model, calibration and validation, sensitivity tests, model application and Federal peer review results. We conclude that it is possible to create and apply a regional demand model system using parcel-level geography and half-hour time of day periods. Experiences thus far have pointed to major benefits of using detailed land use variables and urban design variables, but also to new challenges in providing parcel-level land use inputs for future years.},
  author = {Bradley, Mark and Bowman, John L. and Griesenbeck, Bruce},
  doi = {10.1016/S1755-5345(13)70027-7},
  isbn = {17555345},
  issn = {17555345},
  journal = {Journal of Choice Modelling},
  keywords = {Activity-based models,Microsimulation,Travel demand forecasting},
  number = {1},
  pages = {5--31},
  title = {{SACSIM: An applied activity-based model system with fine-level spatial and temporal resolution}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1755534513700277},
  volume = {3},
  year = {2010}
}
@inproceedings{Zheng2010,
  abstract = {With the increasing popularity of location-based services, such as tour guide and location-based social network, we now have accumulated many location data on the Web. In this paper, we show that, by using the location data based on GPS and users comments at various locations, we can discover interesting locations and possible activities that can be performed there for recommendations. Our research is highlighted in the following location-related queries in our daily life: 1) if we want to do something such as sightseeing or food-hunting in a large city such as Beijing, where should we go? 2) If we have already visited some places such as the Birds Nest building in Beijings Olympic park, what else can we do there? By using our system, for the first question, we can recommend her to visit a list of interesting locations such as Tiananmen Square, Birds Nest, etc. For the second question, if the user visits Birds Nest, we can recommend her to not only do sightseeing but also to experience its outdoor exercise facilities or try some nice food nearby. To achieve this goal, we first model the users location and activity histories that we take as input. We then mine knowledge, such as the location features and activity-activity correlations from the geographical databases and the Web, to gather additional inputs. Finally, we apply a collective matrix factorization method to mine interesting locations and activities, and use them to recommend to the users where they can visit if they want to perform some specific activities and what they can do if they visit some specific places. We empirically evaluated our system using a large GPS dataset collected by 162 users over a period of 2.5 years in the real-world. We extensively evaluated our system and showed that our system can outperform several state-of-the-art baselines.},
  address = {New York, New York, USA},
  author = {Zheng, Vincent W. and Zheng, Yu and Xie, Xing and Yang, Qiang},
  booktitle = {Proceedings of the 19th international conference on World wide web - WWW '10},
  doi = {10.1145/1772690.1772795},
  isbn = {9781605587998},
  pages = {1029},
  publisher = {ACM Press},
  title = {{Collaborative location and activity recommendations with GPS history data}},
  url = {http://portal.acm.org/citation.cfm?doid=1772690.1772795},
  year = {2010}
}
@article{Song2010a,
  abstract = {While the fat tailed jump size and the waiting time distributions characterizing individual human trajectories strongly suggest the relevance of the continuous time random walk (CTRW) models of human mobility, no one seriously believes that human traces are truly random. Given the importance of human mobility, from epidemic modeling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model not only accounts for the empirically observed scaling laws but also allows us to analytically predict most of the pertinent scaling exponents.},
  archiveprefix = {arXiv},
  arxivid = {1010.0436},
  author = {Song, Chaoming and Koren, Tal and Wang, Pu and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1038/nphys1760},
  eprint = {1010.0436},
  isbn = {1745-2473},
  issn = {17452473},
  journal = {Nature Physics},
  month = {oct},
  number = {10},
  pages = {818--823},
  title = {{Modelling the scaling properties of human mobility}},
  url = {http://www.nature.com/articles/nphys1760},
  volume = {6},
  year = {2010}
}
@article{Ratti2010,
  abstract = {Do regional boundaries defined by governments respect the more natural ways that people interact across space? This paper proposes a novel, fine-grained approach to regional delineation, based on analyzing networks of billions of individual human transactions. Given a geographical area and some measure of the strength of links between its inhabitants, we show how to partition the area into smaller, non-overlapping regions while minimizing the disruption to each person's links. We tested our method on the largest non-Internet human network, inferred from a large telecommunications database in Great Britain. Our partitioning algorithm yields geographically cohesive regions that correspond remarkably well with administrative regions, while unveiling unexpected spatial structures that had previously only been hypothesized in the literature. We also quantify the effects of partitioning, showing for instance that the effects of a possible secession of Wales from Great Britain would be twice as disruptive for the human network than that of Scotland.},
  author = {Ratti, Carlo and Sobolevsky, Stanislav and Calabrese, Francesco and Andris, Clio and Reades, Jonathan and Martino, Mauro and Claxton, Rob and Strogatz, Steven H.},
  doi = {10.1371/journal.pone.0014248},
  editor = {Sporns, Olaf},
  isbn = {1932-6203},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {dec},
  number = {12},
  pages = {e14248},
  pmid = {21170390},
  title = {{Redrawing the map of Great Britain from a network of human interactions}},
  url = {http://dx.plos.org/10.1371/journal.pone.0014248},
  volume = {5},
  year = {2010}
}
@article{Thiemann2010,
  abstract = {Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity.},
  archiveprefix = {arXiv},
  arxivid = {1001.0943},
  author = {Thiemann, Christian and Theis, Fabian and Grady, Daniel and Brune, Rafael and Brockmann, Dirk},
  doi = {10.1371/journal.pone.0015422},
  editor = {de Polavieja, Gonzalo},
  eprint = {1001.0943},
  isbn = {1932-6203 (Electronic)$\backslash$r1932-6203 (Linking)},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {nov},
  number = {11},
  pages = {e15422},
  pmid = {21124970},
  title = {{The structure of borders in a small world}},
  url = {http://dx.plos.org/10.1371/journal.pone.0015422},
  volume = {5},
  year = {2010}
}
@incollection{Brockmann2010,
  abstract = {Summary This chapter contains sections titled: Introduction and Motivation Quantitative Assessments of Human Mobility Statistical Properties and Scaling Laws in Multi-Scale Mobility Networks Spatially Extended Epidemic Models Spatial Models References},
  address = {Weinheim, Germany},
  author = {Brockmann, Dirk},
  booktitle = {Reviews of Nonlinear Dynamics and Complexity},
  doi = {10.1002/9783527628001.ch1},
  isbn = {9783527408504},
  keywords = {Epidemic models,Human mobility,Multi-scale mobility networks,Scaling laws,Spatial disease dynamics,Spatial models,Statistical properties},
  month = {jun},
  pages = {1--24},
  publisher = {Wiley-VCH Verlag GmbH {\&} Co. KGaA},
  title = {{Human Mobility and Spatial Disease Dynamics}},
  url = {http://doi.wiley.com/10.1002/9783527628001.ch1},
  volume = {2},
  year = {2010}
}
@inproceedings{Vieira2010b,
  abstract = {The recent adoption of ubiquitous computing technologies (e.g. GPS, WLAN networks) has enabled capturing large amounts of spatio-temporal data about human motion. The digital footprints computed from these datasets provide complementary information for the study of social and human dynamics, with applications ranging from urban planning to transportation and epidemiology. A common problem for all these applications is the detection of dense areas, i.e. areas where individuals concentrate within a specific geographical region and time period. Nevertheless, the techniques used so far face an important limitation: they tend to identify as dense areas regions that do not respect the natural tessellation of the underlying space. In this paper, we propose a novel technique, called DADMST, to detect dense areas based on the Maximum Spanning Tree (MST) algorithm applied over the communication antennas of a cell phone infrastructure. We evaluate and validate our approach with a real dataset containing the Call Detail Records (CDR) of over one million individuals, and apply the methodology to study social dynamics in an urban environment.},
  author = {Vieira, Marcos R. and Fr{\'{i}}as-Mart{\'{i}}nez, Vanessa and Oliver, Nuria and Fr{\'{i}}as-Mart{\'{i}}nez, Enrique},
  booktitle = {Proceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust},
  doi = {10.1109/SocialCom.2010.41},
  isbn = {9780769542119},
  month = {aug},
  pages = {241--248},
  publisher = {IEEE},
  title = {{Characterizing dense urban areas from mobile phone-call data: Discovery and social dynamics}},
  url = {http://ieeexplore.ieee.org/document/5590404/},
  year = {2010}
}
@article{Centola2010,
  abstract = {How do social networks affect the spread of behavior? A popular hypothesis states that networks with many clustered ties and a high degree of separation will be less effective for behavioral diffusion than networks in which locally redundant ties are rewired to provide shortcuts across the social space. A competing hypothesis argues that when behaviors require social reinforcement, a network with more clustering may be more advantageous, even if the network as a whole has a larger diameter. I investigated the effects of network structure on diffusion by studying the spread of health behavior through artificially structured online communities. Individual adoption was much more likely when participants received social reinforcement from multiple neighbors in the social network. The behavior spread farther and faster across clustered-lattice networks than across corresponding random networks.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1011.1669v3},
  author = {Centola, Damon},
  doi = {10.1126/science.1185231},
  eprint = {arXiv:1011.1669v3},
  isbn = {3295996119},
  issn = {10959203},
  journal = {Science},
  month = {sep},
  number = {5996},
  pages = {1194--1197},
  pmid = {20813952},
  title = {{The spread of behavior in an online social network experiment}},
  url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1185231},
  volume = {329},
  year = {2010}
}
@inproceedings{Vieira2010,
  abstract = {The wide adaptation of GPS and cellular technologies has created many applications that collect and maintain large repositories of data in the form of trajectories. Previous work on querying/analyzing trajectorial data typically falls intomethods that either address spatial range and NN queries, or, similarity based queries. Nevertheless, trajectories are complex objects whose behavior over time and space can be better captured as a sequence of interesting events. We thus facilitate the use of motion “pattern” queries which al- low the user to select trajectories based on specific motion patterns. Such patterns are described as regular expressions over a spatial alphabet that can be implicitly or explicitly anchored to the time domain. Moreover, we are interested in “flexible” patterns that allow the user to include “variables” in the query pattern and thus greatly increase its expressive power. In this paper we introduce a framework for efficient processing of flexible pattern queries. The framework in- cludes an underlying indexing structure and algorithms for query processing using different evaluation strategies. An extensive performance evaluation of this framework shows significant performance improvement when compared to ex- isting solutions.},
  address = {New York, New York, USA},
  author = {Vieira, Marcos R and Bakalov, Petko and Tsotras, Vassilis J},
  booktitle = {Proceedings of the 13th International Conference on Extending Database Technology - EDBT '10},
  doi = {10.1145/1739041.1739091},
  isbn = {9781605589459},
  pages = {406},
  publisher = {ACM Press},
  title = {{Querying trajectories using flexible patterns}},
  url = {http://portal.acm.org/citation.cfm?doid=1739041.1739091},
  year = {2010}
}
@inproceedings{Vieira2010a,
  abstract = {Call Detail Record (CDR) databases contain mil- lions of records with information about cell phone calls, including the position of the user when the call was made/received. This huge amount of spatiotemporal data opens the door for the study of human trajectories on a large scale without the bias that other sources (like GPS or WLAN networks) introduce in the population studied. Also, it provides a platform for the development of a wide variety of studies ranging from the spread of diseases to planning of public transport. Nevertheless, previous work on spatiotemporal queries does not provide a framework flexible enough for expressing the complexity of human trajectories. In this paper we present the Spatiotemporal Pattern System (STPS) to query spatiotemporal patterns in very large CDR databases. STPS defines a regular-expression query language that is intuitive and that allows for any combination of spatial and temporal predicates with constraints, including the use of variables. The design of the language took into consideration the layout of the areas being covered by the cellular towers, as well as “areas” that label places of interested (e.g. neighborhoods, parks, etc) and topological operators. STPS includes an underlying indexing structure and algorithms for query processing using different evaluation strategies. A full implementation of the STPS is currently running with real, very large CDR databases on Telef´ onica Research Labs. An extensive performance evaluation of the STPS shows that it can efficiently find complex mobility patterns in large CDR databases.},
  author = {Vieira, Marcos R. and Fr{\'{i}}as-Mart{\'{i}}nez, Enrique and Bakalov, Petko and Fr{\'{i}}as-Mart{\'{i}}nez, Vanessa and Tsotras, Vassilis J.},
  booktitle = {Proceedings - IEEE International Conference on Mobile Data Management},
  doi = {10.1109/MDM.2010.24},
  isbn = {9780769540481},
  issn = {15516245},
  pages = {239--248},
  publisher = {IEEE},
  title = {{Querying spatio-temporal patterns in mobile phone-call databases}},
  url = {http://ieeexplore.ieee.org/document/5489659/},
  year = {2010}
}
@inproceedings{Blumenstock2010,
  address = {New York, NY, USA},
  author = {Blumenstock, Joshua and Eagle, Nathan},
  booktitle = {Proc. of the 4th ACM/IEEE Int. Conf. on Inf. and Comm. Tech. and Devel.},
  doi = {10.1145/2369220.2369225},
  isbn = {9781450307871},
  keywords = {CDR,ICTD,Rwanda,call detail records,mobile phones,phone survey},
  pages = {1--10},
  publisher = {ACM Press},
  title = {{Mobile divides}},
  url = {http://dl.acm.org/citation.cfm?doid=2369220.2369225},
  year = {2010}
}
@article{Frias-Martinez2010,
  abstract = {The gender divide in the access to technology in developing economies makes gender characterization and automatic gender identification two of the most critical needs for improving cell phone-based services. Gender identification has been typically solved using voice or image processing. However, such techniques cannot be applied to cell phone networks mostly due to privacy concerns. In this paper, we present a study aimed at characterizing and automatically identifying the gender of a cell phone user in a developing economy based on behavioral, social and mobility variables. Our contributions are twofold: (1) understanding the role that gender plays on phone usage, and (2) evaluating common machine learning approaches for gender identification. The analysis was carried out using the encrypted CDRs (Call Detail Records) of approximately 10, 000 users from a developing economy, whose gender was known a priori. Our results indicate that behavioral and social variables, including the number of input/output calls and the in degree/out degree of the social network, reveal statistically significant differences between male and female callers. Finally, we propose a new gender identification algorithm that can achieve classification rates of up to 80{\%} when the percentage of predicted instances is reduced.},
  author = {Frias-Martinez, V and Frias-Martinez, E and Oliver, Nuria},
  file = {::},
  isbn = {9781577354550},
  journal = {Intelligence for Development},
  keywords = {Technical Report SS-10-01},
  pages = {37--42},
  title = {{A Gender-Centric Analysis of Calling Behavior in a Developing Economy Using Call Detail Records.}},
  url = {http://www.aaai.org/ocs/index.php/SSS/SSS10/paper/viewFile/1094/1347},
  year = {2010}
}
@article{Eagle2010,
  abstract = {Network diversity yields context-dependent benefits that are not yet fully-understood. I elaborate on a recently introduced distinction between tie strength diversity and information source diversity, and explain when, how, and why they matter. The issue whether there are benefits to specialization is the key.},
  archiveprefix = {arXiv},
  arxivid = {1011.0208},
  author = {Eagle, Nathan and Macy, Michael and Claxton, Rob},
  doi = {10.1126/science.1186605},
  eprint = {1011.0208},
  isbn = {1095-9203 (Electronic)$\backslash$r0036-8075 (Linking)},
  issn = {00368075},
  journal = {Science},
  month = {may},
  number = {5981},
  pages = {1029--1031},
  pmid = {20489022},
  title = {{Network diversity and economic development}},
  url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1186605},
  volume = {328},
  year = {2010}
}
@article{Peruani2013,
  abstract = {Without having direct access to the information that is being exchanged, traces of information flow can be obtained by looking at temporal sequences of user interactions. These sequences can be represented as causality trees whose statistics result from a complex interplay between the topology of the underlying (social) network and the time correlations among the communications. Here, we study causality trees in mobile-phone data, which can be represented as a dynamical directed network. This representation of the data reveals the existence of super-spreaders and super-receivers. We show that the tree statistics, respectively the information spreading process, are extremely sensitive to the in-out degree correlation exhibited by the users. We also learn that a given information, e.g., a rumor, would require users to retransmit it for more than 30 hours in order to cover a macroscopic fraction of the system. Our analysis indicates that topological node-node correlations of the underlying social network, while allowing the existence of information loops, they also promote information spreading. Temporal correlations, and therefore causality effects, are only visible as local phenomena and during short time scales. Consequently, the very idea that there is (intentional) information spreading beyond a small vecinity is called into question. These results are obtained through a combination of theory and data analysis techniques.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1302.0274v1},
  author = {Peruani, Fernando and Tabourier, Lionel},
  doi = {10.1371/journal.pone.0028860},
  eprint = {arXiv:1302.0274v1},
  file = {::},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {feb},
  number = {12},
  pmid = {22216128},
  title = {{Directedness of information flow in mobile phone communication networks}},
  url = {http://arxiv.org/abs/1302.0274 http://dx.doi.org/10.1371/journal.pone.0028860},
  volume = {6},
  year = {2011}
}
@article{Hung2011,
  abstract = {Mobile computing systems usually express a user movement trajectory as a sequence of areas that capture the user movement trace. Given a set of user movement trajectories, user movement patterns refer to the sequences of areas through which a user frequently travels. In an attempt to obtain user movement patterns for mobile applications, prior studies explore the problem of mining user movement patterns from the movement logs of mobile users. These movement logs generate a data record whenever a mobile user crosses base station coverage areas. However, this type of movement log does not exist in the system and thus generates extra overheads. By exploiting an existing log, namely, call detail records, this article proposes a Regression-based approach for mining User Movement Patterns (abbreviated as RUMP). This approach views call detail records as random sample trajectory data, and thus, user movement patterns are represented as movement functions in this article. We propose algorithm LS (standing for Large Sequence) to extract the call detail records that capture frequent user movement behaviors. By exploring the spatio-temporal locality of continuous movements (i.e., a mobile user is likely to be in nearby areas if the time interval between consecutive calls is small), we develop algorithm TC (standing for Time Clustering) to cluster call detail records. Then, by utilizing regression analysis, we develop algorithm MF (standing for Movement Function) to derive movement functions. Experimental studies involving both synthetic and real datasets show that RUMP is able to derive user movement functions close to the frequent movement behaviors of mobile users. {\textcopyright} 2010 Elsevier B.V. All rights reserved.},
  author = {Hung, Chih Chieh and Peng, Wen Chih},
  doi = {10.1016/j.datak.2010.07.010},
  issn = {0169023X},
  journal = {Data and Knowledge Engineering},
  keywords = {Data mining,Mobile data management,User movement patterns},
  month = {jan},
  number = {1},
  pages = {1--20},
  title = {{A regression-based approach for mining user movement patterns from random sample data}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0169023X10000923},
  volume = {70},
  year = {2011}
}
@inproceedings{Cho2011,
  abstract = {Even though human movement and mobility patterns have a high degree of freedom and variation; as well as data from two online location-based social networks; they also exhibit structural patterns due to geographic and social constraints. Using cell phone location data; we aim to understand what basic laws govern human motion and dynamics. We find that humans experience a combination of periodic movement that is geographically limited and seemingly random jumps correlated with their social networks. Short-ranged travel is periodic both spatially and temporally and not effected by the social network structure; we develop a model of human mobility that combines periodic short range movements with travel due to the social network structure. We show that our model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance than present models of human mobility.; while long-distance travel is more influenced by social network ties. We show that social relationships can explain about 10{\%} to 30{\%} of all human movement; while periodic behavior explains 50{\%} to 70{\%}. Based on our findings},
  address = {New York, New York, USA},
  author = {Cho, Eunjoon and Myers, Seth A. and Leskovec, Jure},
  booktitle = {Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11},
  doi = {10.1145/2020408.2020579},
  isbn = {9781450308137},
  issn = {9781412946452},
  pages = {1082},
  publisher = {ACM Press},
  title = {{Friendship and mobility}},
  url = {http://dl.acm.org/citation.cfm?doid=2020408.2020579},
  year = {2011}
}
@article{Zhang2011,
  author = {Hua, Xian-Sheng and Tian, Qi and {Del Bimbo}, Alberto and Jain, Ramesh},
  doi = {10.1145/1899412.1899413},
  issn = {21576904},
  journal = {ACM Transactions on Intelligent Systems and Technology},
  month = {jan},
  number = {2},
  pages = {1--2},
  title = {{Introduction to the special issue on intelligent multimedia systems and technology}},
  url = {http://dl.acm.org/citation.cfm?doid=1889681.1889682},
  volume = {2},
  year = {2011}
}
@inproceedings{Wang2011,
  abstract = {Our understanding of how individual mobility patterns shape and impact the social network is limited, but is essential for a deeper understanding of network dynamics and evo- lution. This question is largely unexplored, partly due to the diculty in obtaining large-scale society-wide data that simultaneously capture the dynamical information on indi- vidual movements and social interactions. Here we address this challenge for the rst time by tracking the trajecto- ries and communication records of 6 Million mobile phone users. We nd that the similarity between two individuals' movements strongly correlates with their proximity in the social network. We further investigate how the predictive power hidden in such correlations can be exploited to ad- dress a challenging problem: which new links will develop in a social network. We show that mobility measures alone yield surprising predictive power, comparable to traditional network-based measures. Furthermore, the prediction accu- racy can be signi cantly improved by learning a supervised classi er based on combined mobility and network measures. We believe our ndings on the interplay of mobility patterns and social ties o er new perspectives on not only link pre- diction but also network dynamics.},
  address = {New York, New York, USA},
  author = {Wang, Dashun and Pedreschi, Dino and Song, Chaoming and Giannotti, Fosca and Barabasi, Albert-Laszlo},
  booktitle = {Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11},
  doi = {10.1145/2020408.2020581},
  isbn = {9781450308137},
  issn = {1450308139},
  pages = {1100},
  publisher = {ACM Press},
  title = {{Human mobility, social ties, and link prediction}},
  url = {http://dl.acm.org/citation.cfm?doid=2020408.2020581},
  year = {2011}
}
@incollection{Wakamiya2011,
  abstract = {It is essential to characterize geographic regions in order to make various geographic decisions. These regions can be characterized from various perspectives such as the physical appearance of a town. In this paper, as a novel approach to characterize geographic regions, we focus on the daily lifestyle patterns of crowds via location-based social networking sites in urban areas. For this purpose, we propose a novel method to characterize urban areas using Twitter, the most representative microblogging site. In order to grasp images of a city by social network based crowds, we define the geographic regularity of the region using daily crowd activity patterns; for instance, the number of tweets, through the number of users, and the movement of the crowds. We also analyze the changing patterns of geographic regularity with time and categorize clustered urban types by tracking common patterns among the regions. Finally, we present examples of several urban types through the observation of experimentally extracted patterns of crowd behavior in actual urban areas.},
  author = {Wakamiya, Shoko and Lee, Ryong and Sumiya, Kazutoshi},
  booktitle = {LNCS},
  doi = {10.1007/978-3-642-20630-6_7},
  isbn = {9783642206290},
  issn = {03029743},
  keywords = {Geographical Regularity,Microblogs,Urban Characteristics},
  pages = {108--123},
  publisher = {Springer},
  title = {{Urban area characterization based on semantics of crowd activities in Twitter}},
  url = {http://link.springer.com/10.1007/978-3-642-20630-6{\_}7},
  volume = {6631},
  year = {2011}
}
@article{Bagrow2011,
  abstract = {Despite recent advances in uncovering the quantitative features of stationary human activity patterns, many applications, from pandemic prediction to emergency response, require an understanding of how these patterns change when the population encounters unfamiliar conditions. To explore societal response to external perturbations we identified real-time changes in communication and mobility patterns in the vicinity of eight emergencies, such as bomb attacks and earthquakes, comparing these with eight non-emergencies, like concerts and sporting events. We find that communication spikes accompanying emergencies are both spatially and temporally localized, but information about emergencies spreads globally, resulting in communication avalanches that engage in a significant manner the social network of eyewitnesses. These results offer a quantitative view of behavioral changes in human activity under extreme conditions, with potential long-term impact on emergency detection and response.},
  archiveprefix = {arXiv},
  arxivid = {1106.0560},
  author = {Bagrow, James P. and Wang, Dashun and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1371/journal.pone.0017680},
  editor = {Moreno, Yamir},
  eprint = {1106.0560},
  isbn = {0011-3891},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {mar},
  number = {3},
  pages = {e17680},
  pmid = {21479206},
  title = {{Collective response of human populations to large-scale emergencies}},
  url = {http://dx.plos.org/10.1371/journal.pone.0017680},
  volume = {6},
  year = {2011}
}
@article{Bengtsson2011,
  abstract = {BACKGROUND: Population movements following disasters can cause important increases in morbidity and mortality. Without knowledge of the locations of affected people, relief assistance is compromised. No rapid and accurate method exists to track population movements after disasters. We used position data of subscriber identity module (SIM) cards from the largest mobile phone company in Haiti (Digicel) to estimate the magnitude and trends of population movements following the Haiti 2010 earthquake and cholera outbreak.$\backslash$n$\backslash$nMETHODS AND FINDINGS: Geographic positions of SIM cards were determined by the location of the mobile phone tower through which each SIM card connects when calling. We followed daily positions of SIM cards 42 days before the earthquake and 158 days after. To exclude inactivated SIM cards, we included only the 1.9 million SIM cards that made at least one call both pre-earthquake and during the last month of study. In Port-au-Prince there were 3.2 persons per included SIM card. We used this ratio to extrapolate from the number of moving SIM cards to the number of moving persons. Cholera outbreak analyses covered 8 days and tracked 138,560 SIM cards. An estimated 630,000 persons (197,484 Digicel SIM cards), present in Port-au-Prince on the day of the earthquake, had left 19 days post-earthquake. Estimated net outflow of people (outflow minus inflow) corresponded to 20{\%} of the Port-au-Prince pre-earthquake population. Geographic distribution of population movements from Port-au-Prince corresponded well with results from a large retrospective, population-based UN survey. To demonstrate feasibility of rapid estimates and to identify areas at potentially increased risk of outbreaks, we produced reports on SIM card movements from a cholera outbreak area at its immediate onset and within 12 hours of receiving data.$\backslash$n$\backslash$nCONCLUSIONS: Results suggest that estimates of population movements during disasters and outbreaks can be delivered rapidly and with potentially high validity in areas with high mobile phone use.},
  author = {Bengtsson, Linus and Lu, Xin and Thorson, Anna and Garfield, Richard and von Schreeb, Johan},
  doi = {10.1371/journal.pmed.1001083},
  editor = {Gething, Peter W.},
  isbn = {1549-1277},
  issn = {15491277},
  journal = {PLoS Medicine},
  month = {aug},
  number = {8},
  pages = {e1001083},
  pmid = {21918643},
  title = {{Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: A post-earthquake geospatial study in haiti}},
  url = {http://dx.plos.org/10.1371/journal.pmed.1001083},
  volume = {8},
  year = {2011}
}
@incollection{Soto2011,
  abstract = {The socioeconomic status of a population or an individual provides an understanding of its access to housing, education, health or basic services like water and electricity. In itself, it is also an indirect indicator of the purchasing power and as such a key element when personalizing the interaction with a customer, especially for marketing campaigns or offers of new products. In this paper we study if the information derived from the aggregated use of cell phone records can be used to identify the socioeconomic levels of a population. We present predictive models constructed with SVMs and Random Forests that use the aggregated behavioral variables of the communication antennas to predict socioeconomic levels. Our results show correct prediction rates of over 80{\%} for an urban population of around 500,000 citizens. {\textcopyright} 2011 Springer-Verlag.},
  author = {Soto, Victor and Frias-Martinez, Vanessa and Virseda, Jesus and Frias-Martinez, Enrique},
  booktitle = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-642-22362-4_35},
  isbn = {9783642223617},
  issn = {03029743},
  pages = {377--388},
  publisher = {Springer},
  title = {{Prediction of socioeconomic levels using cell phone records}},
  url = {http://link.springer.com/10.1007/978-3-642-22362-4{\_}35},
  volume = {6787 LNCS},
  year = {2011}
}
@incollection{Vieira2011,
  abstract = {We describe the FlexTrack system for querying trajectories using flexible pattern queries. Such queries are composed of a sequence of simple spatio-temporal predicates, e.g., range and nearest-neighbors, as well as complex motion pattern predicates, e.g., predicates that contain variables and constraints. Users can interactively select spatio-temporal predicates to construct such pattern queries using a hierarchy of regions that partition the spatial domain. Several different query processing algorithms are currently implemented and available in the FlexTrack system.},
  author = {Vieira, Marcos R. and Bakalov, Petko and Tsotras, Vassilis J.},
  booktitle = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-642-22922-0_34},
  isbn = {9783642229213},
  issn = {03029743},
  pages = {475--480},
  title = {{FlexTrack: A system for querying flexible patterns in trajectory databases}},
  url = {http://link.springer.com/10.1007/978-3-642-22922-0{\_}34},
  volume = {6849 LNCS},
  year = {2011}
}
@article{Meloni2011,
  abstract = {Current modeling of infectious diseases allows for the study of realistic scenarios that include population heterogeneity, social structures, and mobility processes down to the individual level. The advances in the realism of epidemic description call for the explicit modeling of individual behavioral responses to the presence of disease within modeling frameworks. Here we formulate and analyze a metapopulation model that incorporates several scenarios of self-initiated behavioral changes into the mobility patterns of individuals. We find that prevalence-based travel limitations do not alter the epidemic invasion threshold. Strikingly, we observe in both synthetic and data-driven numerical simulations that when travelers decide to avoid locations with high levels of prevalence, this self-initiated behavioral change may enhance disease spreading. Our results point out that the real-time availability of information on the disease and the ensuing behavioral changes in the population may produce a negative impact on disease containment and mitigation.},
  author = {Meloni, Sandro and Perra, Nicola and Arenas, Alex and G{\'{o}}mez, Sergio and Moreno, Yamir and Vespignani, Alessandro},
  doi = {10.1038/srep00062},
  issn = {20452322},
  journal = {Scientific Reports},
  month = {dec},
  number = {1},
  pages = {62},
  pmid = {22355581},
  title = {{Modeling human mobility responses to the large-scale spreading of infectious diseases}},
  url = {http://www.nature.com/articles/srep00062},
  volume = {1},
  year = {2011}
}
@article{Calabrese2011,
  abstract = {{\textless}p{\textgreater}Using an algorithm to analyze opportunistically collected mobile phone location data, the authors estimate weekday and weekend travel patterns of a large metropolitan area with high accuracy.{\textless}/p{\textgreater}},
  author = {Calabrese, Francesco and {Di Lorenzo}, Giusy and Liu, Liang and Ratti, Carlo},
  doi = {10.1109/MPRV.2011.41},
  isbn = {1536-1268},
  issn = {15361268},
  journal = {IEEE Pervasive Computing},
  keywords = {location dependent,location sensitive,pervasive computing,system applications and experience,transportation},
  month = {apr},
  number = {4},
  pages = {36--44},
  title = {{Estimating origin-destination flows using mobile phone location data}},
  url = {http://ieeexplore.ieee.org/document/5871578/},
  volume = {10},
  year = {2011}
}
@inproceedings{Frias-Martinez2012,
  abstract = {The ubiquitous presence of cell phones in emerging economies has brought about a wide range of cell phone-based services for low-income groups. Often times, the success of such technologies highly depends on its adaptation to the needs and habits of each social group. In an attempt to understand how cell phones are being used by citizens in an emerging economy, we present a large-scale study to analyze the relationship between specific socio-economic factors and the way people use cell phones in an emerging economy in Latin America. We propose a novel analytical approach that combines large-scale datasets of cell phone records with countrywide census data to reveal findings at a national level. Our main results show correlations between socio-economic levels and social network or mobility patterns among others. We also provide analytical models to accurately approximate census variables from cell phone records with R 2 ≈ 0:82. Copyright 2012 ACM.},
  address = {New York, New York, USA},
  author = {Frias-Martinez, V and Virseda, J},
  booktitle = {ACM International Conference Proceeding Series},
  doi = {10.1145/2160673.2160684},
  isbn = {9781450310451},
  keywords = {0,Call detail records,Census maps,Sensing human behavior,Socio-economic factors,soc},
  pages = {76--84},
  publisher = {ACM Press},
  title = {{On the relationship between socio-economic factors and cell phone usage}},
  url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84859043183{\&}partnerID=40{\&}md5=e3e0e8ce9d7daba7c25a4d87da8aa254},
  year = {2012}
}
@article{Blumenstock,
  author = {Blumenstock, Joshua Evan and Hall, Mary Gates and Eagle, Nathan},
  journal = {Inf. Technol. Int. Dev.},
  number = {2},
  pages = {1--16},
  title = {{Divided We Call : Disparities in Access and Use of Mobile Phones in Rwanda}},
  volume = {8},
  year = {2012}
}
@article{Jo2011,
  abstract = {The temporal communication patterns of human individuals are known to be inhomogeneous or bursty, which is reflected as the heavy tail behavior in the inter-event time distribution. As the cause of such bursty behavior two main mechanisms have been suggested: a) Inhomogeneities due to the circadian and weekly activity patterns and b) inhomogeneities rooted in human task execution behavior. Here we investigate the roles of these mechanisms by developing and then applying systematic de-seasoning methods to remove the circadian and weekly patterns from the time-series of mobile phone communication events of individuals. We find that the heavy tails in the inter-event time distributions remain robustly with respect to this procedure, which clearly indicates that the human task execution based mechanism is a possible cause for the remaining burstiness in temporal mobile phone communication patterns.},
  archiveprefix = {arXiv},
  arxivid = {1101.0377},
  author = {Jo, Hang Hyun and Karsai, Marton and Kertesz, Janos and Kaski, Kimmo},
  doi = {10.1088/1367-2630/14/1/013055},
  eprint = {1101.0377},
  file = {::},
  isbn = {1367-2630},
  issn = {13672630},
  journal = {New Journal of Physics},
  month = {jan},
  title = {{Circadian pattern and burstiness in mobile phone communication}},
  url = {http://arxiv.org/abs/1101.0377 http://dx.doi.org/10.1088/1367-2630/14/1/013055},
  volume = {14},
  year = {2012}
}
@techreport{Toole2012,
  abstract = {Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from personal GPS devices to mobile phones are collecting massive amounts of data on urban systems. The locations, communications, and activities of millions of people are recorded and stored by new information technologies. This work utilizes novel dynamic data, generated by mobile phone users, to measure spatiotemporal changes in population. In the process, we identify the relationship between land use and dynamic population over the course of a typical week. A machine learning classification algorithm is used to identify clusters of locations with similar zoned uses and mobile phone activity patterns. It is shown that the mobile phone data is capable of delivering useful information on actual land use that supplements zoning regulations.},
  institution = {{arXiv}},
  archiveprefix = {arXiv},
  number = {1207.1115},
  author = {Toole, Jameson L. and Ulm, Michael and Bauer, Dietmar and Gonzalez, Marta C.},
  doi = {10.1145/2346496.2346498},
  eprint = {1207.1115},
  file = {::},
  isbn = {978-1-4503-1542-5},
  month = {jul},
  pmid = {1986018621067952938},
  title = {{Inferring land use from mobile phone activity}},
  url = {http://arxiv.org/abs/1207.1115},
  year = {2012}
}
@inproceedings{Janecek2012,
  address = {New York, New York, USA},
  author = {Janecek, Andreas and Hummel, Karin A. and Valerio, Danilo and Ricciato, Fabio and Hlavacs, Helmut},
  booktitle = {Proceedings of the 2012 ACM Conference on Ubiquitous Computing - UbiComp '12},
  doi = {10.1145/2370216.2370272},
  isbn = {9781450312240},
  pages = {361},
  publisher = {ACM Press},
  title = {{Cellular data meet vehicular traffic theory}},
  url = {http://dl.acm.org/citation.cfm?doid=2370216.2370272},
  year = {2012}
}
@incollection{Fiadino2012,
  author = {Fiadino, Pierdomenico and Valerio, Danilo and Ricciato, Fabio and Hummel, Karin Anna},
  booktitle = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-642-28534-9_7},
  isbn = {9783642285332},
  issn = {03029743},
  pages = {66--80},
  title = {{Steps towards the extraction of vehicular mobility patterns from 3G signaling data}},
  url = {http://link.springer.com/10.1007/978-3-642-28534-9{\_}7},
  volume = {7189 LNCS},
  year = {2012},
  publisher = {Springer--Verlag}
}
@article{Zhang2012,
  author = {Zhang, Daqiang and Vasilakos, Athanasios V. and Xiong, Haoyi},
  doi = {10.1145/2377677.2377738},
  isbn = {9781450314190},
  issn = {01464833},
  journal = {ACM SIGCOMM Computer Communication Review},
  month = {sep},
  number = {4},
  pages = {295},
  title = {{Predicting location using mobile phone calls}},
  url = {http://dl.acm.org/citation.cfm?doid=2377677.2377738},
  volume = {42},
  year = {2012}
}
@article{Yuan2012a,
  abstract = {Information and communication technologies (ICTs), such as mobile phones and the Internet, are increasingly pervasive in modern society. These technologies provide new resources for spatio-temporal data mining and geographic knowledge discovery. Since the development of ICTs also impacts physical movement of individuals in societies, much of the existing research has focused on examining the correlation between ICT and human mobility. In this paper, we aim to provide a deeper understanding of how usage of mobile phones correlates with individual travel behavior by exploring the correlation between mobile phone call frequencies and three indicators of travel behavior: (1) radius, (2) eccentricity, and (3) entropy. The methodology is applied to a large dataset from Harbin city in China. The statistical analysis indicates a significant correlation between mobile phone usage and all of the three indicators. In addition, we examine and demonstrate how explanatory factors, such as age, gender, social temporal orders and characteristics of the built environment, impact the relationship between mobile phone usage and individual activity behavior. {\textcopyright} 2011 Elsevier Ltd.},
  author = {Yuan, Yihong and Raubal, Martin and Liu, Yu},
  doi = {10.1016/j.compenvurbsys.2011.07.003},
  isbn = {0198-9715},
  issn = {01989715},
  journal = {Computers, Environment and Urban Systems},
  keywords = {Geographic knowledge discovery,Human mobility,Information and communication technologies (ICTs),Mobile phone},
  month = {mar},
  number = {2},
  pages = {118--130},
  title = {{Correlating mobile phone usage and travel behavior - A case study of Harbin, China}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0198971511000652},
  volume = {36},
  year = {2012}
}
@article{Wang2012,
  abstract = {In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own--surprisingly few--driver sources. Based on this finding we propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.},
  archiveprefix = {arXiv},
  arxivid = {1212.5327},
  author = {Wang, Pu and Hunter, Timothy and Bayen, Alexandre M. and Schechtner, Katja and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1038/srep01001},
  eprint = {1212.5327},
  isbn = {2045-2322 (Electronic)$\backslash$r2045-2322 (Linking)},
  issn = {20452322},
  journal = {Scientific Reports},
  month = {dec},
  number = {1},
  pages = {1001},
  pmid = {23259045},
  title = {{Understanding road usage patterns in urban areas}},
  url = {http://www.nature.com/articles/srep01001},
  volume = {2},
  year = {2012}
}
@article{Elwood2012,
  abstract = {The convergence of newly interactiveWeb-based technologies with growing practices of user-generated content disseminated on the Internet is generating a remarkable new form of geographic information. Citizens are using handheld devices to collect geographic information and contribute it to crowd-sourced data sets, usingWeb-based mapping interfaces to mark and annotate geographic features, or adding geographic location to photographs, text, and other media shared online. These phenomena, which generate what we refer to collectively as volunteered geographic information (VGI), represent a paradigmatic shift in how geographic information is created and shared and by whom, as well as its content and characteristics. This article, which draws on our recently completed inventory of VGI initiatives, is intended to frame the crucial dimensions of VGI for geography and geographers, with an eye toward identifying its potential in our field, as well as themost pressing research needed to realize this potential. Drawing on our ongoing research, we examine the content and characteristics of VGI, the technical and social processes through which it is produced, appropriate methods for synthesizing and using these data in research, and emerging social and political concerns related to this new form of information. Key Words: GeospatialWeb, neogeography, spatial data infrastructure, volunteered geographic information, Web 2.0.},
  author = {Elwood, Sarah and Goodchild, Michael F. and Sui, Daniel Z.},
  doi = {10.1080/00045608.2011.595657},
  isbn = {0004-5608$\backslash$n1467-8306},
  issn = {00045608},
  journal = {Annals of the Association of American Geographers},
  keywords = {Geospatial Web,Web 2.0,neogeography,spatial data infrastructure,volunteered geographic information},
  month = {may},
  number = {3},
  pages = {571--590},
  title = {{Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice}},
  url = {http://www.tandfonline.com/doi/abs/10.1080/00045608.2011.595657},
  volume = {102},
  year = {2012}
}
@article{Jiang2012,
  abstract = {Data mining and statistical learning techniques are powerful analysis tools yet to be incorporated in the domain of urban studies and transportation research. In this work, we analyze an activity-based travel survey conducted in the Chicago metropolitan area over a demographic representative sample of its population. Detailed data on activities by time of day were collected from more than 30,000 individuals (and 10,552 households) who participated in a 1-day or 2-day survey implemented from January 2007 to February 2008. We examine this large-scale longitudinal data in order to explore three critical issues: (1) the inherent daily activity structure of individuals in a metropolitan area, (2) the variation of individual daily activities?how they grow and fade over time, and (3) clusters of individual behaviors and the revelation of their related socio-demographic information. We find that the population can be clustered into 8 and 7 representative groups according to their activities during weekdays and weekends, respectively. Our results enrich the traditional divisions consisting of only three groups (workers, students and non-workers) and provide clusters based on activities of different time of day. The generated clusters combined with social demographic information provide a new perspective for urban and transportation planning as well as for emergency response and spreading dynamics, by addressing when, where, and how individuals interact with places in metropolitan areas.},
  author = {Jiang, Shan and Ferreira, Joseph and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1007/s10618-012-0264-z},
  isbn = {1384-5810},
  issn = {13845810},
  journal = {Data Mining and Knowledge Discovery},
  keywords = {Daily activity clustering,Eigen decomposition,Human activity,Metropolitan area,Statistical learning},
  month = {nov},
  number = {3},
  pages = {478--510},
  title = {{Clustering daily patterns of human activities in the city}},
  url = {http://link.springer.com/10.1007/s10618-012-0264-z},
  volume = {25},
  year = {2012}
}
@article{Kang2012,
  abstract = {This paper provides a new perspective on human motion with an investigation of whether and how patterns of human mobility inside cities are affected by two urban morphological characteristics: compactness and size. Mobile phone data have been collected in eight cities in Northeast China and used to extract individuals' movement trajectories. The massive mobile phone data provides a wide coverage and detailed depiction of individuals' movement in space and time. Considering that most individuals' movement is limited within particular urban areas, boundaries of urban agglomerations are demarcated based on the spatial distribution of mobile phone base towers. Results indicate that the distribution of human's intra-urban travel in general follows the exponential law. The exponents, however, vary from city to city and indicate the impact of city sizes and shapes. Individuals living in large or less compact cities generally need to travel farther on a daily basis, and vice versa. A Monte Carlo simulation analysis based on Levy flight is conducted to further examine and validate the relation between intra-urban human mobility and urban morphology. {\textcopyright} 2011 Elsevier B.V. All rights reserved.},
  author = {Kang, Chaogui and Ma, Xiujun and Tong, Daoqin and Liu, Yu},
  doi = {10.1016/j.physa.2011.11.005},
  isbn = {0378-4371},
  issn = {03784371},
  journal = {Physica A: Statistical Mechanics and its Applications},
  keywords = {Intra-urban human mobility,Monte Carlo simulation,Spatial heterogeneity constrained Levy flight mode,Urban morphology},
  month = {feb},
  number = {4},
  pages = {1702--1717},
  title = {{Intra-urban human mobility patterns: An urban morphology perspective}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0378437111008405},
  volume = {391},
  year = {2012}
}
@inproceedings{Frias-Martinez2012a,
  abstract = {Commuting matrices are key for a variety of fields, including transportation engineering and urban planning. Up to now, these matrices have been typically generated from data obtained from surveys. Nevertheless, such approaches typically involve high costs which limits the frequency of the studies. Cell phones can be considered one of the main sensors of human behavior due to its ubiquity, and as a such, a pervasive source of mobility information at a large scale. In this paper we propose a new technique for the estimation of commuting matrices using the data collected from the pervasive infrastructure of a cell phone network. Our goal is to show that we can construct cell-phone generated matrices that capture the same patterns as traditional commuting matrices. In order to do so we use optimization techniques in combination with a variation of Temporal Association Rules. Our validation results show that it is possible to construct commuting matrices from call detail records with a high degree of accuracy, and as a result our technique is a cost-effective solution to complement traditional approaches. {\textcopyright} 2012 ACM.},
  address = {New York, New York, USA},
  author = {Frias-Martinez, Vanessa and Soguero, Cristina and Frias-Martinez, Enrique},
  booktitle = {Proceedings of the ACM SIGKDD International Workshop on Urban Computing - UrbComp '12},
  doi = {10.1145/2346496.2346499},
  isbn = {9781450315425},
  issn = {1450315429},
  pages = {9},
  publisher = {ACM Press},
  title = {{Estimation of urban commuting patterns using cellphone network data}},
  url = {http://dl.acm.org/citation.cfm?doid=2346496.2346499},
  year = {2012}
}
@inproceedings{Yuan2012,
  abstract = {The development of a city gradually fosters different functional re- gions, such as educational areas and business districts. In this paper, we propose a framework (titled DRoF) that Discovers Regions of different Functions in a city using both human mobility among re- gions and points of interests (POIs) located in a region. Specifically, we segment a city into disjointed regions according to major roads, such as highways and urban express ways. We infer the functions of each region using a topic-based inference model, which regards a region as a document, a function as a topic, categories of POIs (e.g., restaurants and shopping malls) as metadata (like authors, af- filiations, and key words), and human mobility patterns (when peo- ple reach/leave a region and where people come from and leave for) as words. As a result, a region is represented by a distribution of functions, and a function is featured by a distribution of mobility patterns. We further identify the intensity of each function in differ- ent locations. The results generated by our framework can benefit a variety of applications, including urban planning, location choos- ing for a business, and social recommendations. We evaluated our method using large-scale and real-world datasets, consisting of two POI datasets of Beijing (in 2010 and 2011) and two 3-month GPS trajectory datasets (representing human mobility) generated by over 12,000 taxicabs in Beijing in 2010 and 2011 respectively. The re- sults justify the advantages of our approach over baseline methods solely using POIs or human mobility.},
  address = {New York, New York, USA},
  archiveprefix = {arXiv},
  arxivid = {1010.0436},
  author = {Yuan, Jing and Zheng, Yu and Xie, Xing},
  booktitle = {Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12},
  doi = {10.1145/2339530.2339561},
  eprint = {1010.0436},
  isbn = {9781450314626},
  issn = {1450314627},
  pages = {186},
  pmid = {25716185},
  publisher = {ACM Press},
  title = {{Discovering regions of different functions in a city using human mobility and POIs}},
  url = {http://dl.acm.org/citation.cfm?doid=2339530.2339561},
  year = {2012}
}
@inproceedings{Toole2012a,
  abstract = {Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from personal GPS devices to mobile phones are collecting massive amounts of data on urban systems. The locations, communications, and activities of millions of people are recorded and stored by new information technologies. This work utilizes novel dynamic data, generated by mobile phone users, to measure spatiotemporal changes in population. In the process, we identify the relationship between land use and dynamic population over the course of a typical week. A machine learning classification algorithm is used to identify clusters of locations with similar zoned uses and mobile phone activity patterns. It is shown that the mobile phone data is capable of delivering useful information on actual land use that supplements zoning regulations.},
  address = {New York, New York, USA},
  archiveprefix = {arXiv},
  arxivid = {1207.1115},
  author = {Toole, Jameson L. and Ulm, Michael and Bauer, Dietmar and Gonzalez, Marta C.},
  booktitle = {Proceedings of the ACM SIGKDD International Workshop on Urban Computing - UrbComp '12},
  doi = {10.1145/2346496.2346498},
  eprint = {1207.1115},
  isbn = {978-1-4503-1542-5},
  pages = {1},
  pmid = {1986018621067952938},
  publisher = {ACM Press},
  title = {{Inferring land use from mobile phone activity}},
  url = {http://arxiv.org/abs/1207.1115},
  year = {2012}
}
@inproceedings{Wei2012,
  abstract = {The advances in location-acquisition technologies have led to a myriad of spatial trajectories. These trajectories are usually generated at a low or an irregular frequency due to applications' characteristics or energy saving, leaving the routes between two consecutive points of a single trajectory uncertain (called an uncertain trajectory). In this paper, we present a Route Inference framework based on Collective Knowledge (abbreviated as RICK) to construct the popular routes from uncertain trajectories. Explicitly, given a location sequence and a time span, the RICK is able to construct the top-k routes which sequentially pass through the locations within the specified time span, by aggregating such uncertain trajectories in a mutual reinforcement way (i.e., uncertain + uncertain → certain). Our work can benefit trip planning, traffic management, and animal movement studies. The RICK comprises two components: routable graph construction and route inference. First, we explore the spatial and temporal characteristics of uncertain trajectories and construct a routable graph by collaborative learning among the uncertain trajectories. Second, in light of the routable graph, we propose a routing algorithm to construct the top-k routes according to a user- specified query. We have conducted extensive experiments on two real datasets, consisting of Foursquare check-in datasets and taxi trajectories. The results show that RICK is both effective and efficient.},
  address = {New York, New York, USA},
  author = {Wei, Ling-Yin and Zheng, Yu and Peng, Wen-Chih},
  booktitle = {Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12},
  doi = {10.1145/2339530.2339562},
  isbn = {9781450314626},
  issn = {9781450314626},
  pages = {195},
  pmid = {258205200001},
  publisher = {ACM Press},
  title = {{Constructing popular routes from uncertain trajectories}},
  url = {http://dl.acm.org/citation.cfm?doid=2339530.2339562},
  year = {2012}
}
@article{Gallup2012,
  abstract = {Pedestrian crowds can form the substrate of important socially contagious behaviors, including propagation of visual attention, violence, opinions, and emotional state. However, relating individual to collective behavior is often difficult, and quantitative studies have largely used laboratory experimentation. We present two studies in which we tracked the motion and head direction of 3,325 pedestrians in natural crowds to quantify the extent, influence, and context dependence of socially transmitted visual attention. In our first study, we instructed stimulus groups of confederates within a crowd to gaze up to a single point atop of a building. Analysis of passersby shows that visual attention spreads unevenly in space and that the probability of pedestrians adopting this behavior increases as a function of stimulus group size before saturating for larger groups. We develop a model that predicts that this gaze response will lead to the transfer of visual attention between crowd members, but it is not sufficiently strong to produce a tipping point or critical mass of gaze-following that has previously been predicted for crowd dynamics. A second experiment, in which passersby were presented with two stimulus confederates performing suspicious/irregular activity, supports the predictions of our model. This experiment reveals that visual interactions between pedestrians occur primarily within a 2-m range and that gaze-copying, although relatively weak, can facilitate response to relevant stimuli. Although the above aspects of gaze-following response are reproduced robustly between experimental setups, the overall tendency to respond to a stimulus is dependent on spatial features, social context, and sex of the passerby.},
  author = {Gallup, A. C. and Hale, J. J. and Sumpter, D. J. T. and Garnier, S. and Kacelnik, A. and Krebs, J. R. and Couzin, I. D.},
  doi = {10.1073/pnas.1116141109},
  isbn = {1091-6490 (Electronic)$\backslash$r0027-8424 (Linking)},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {may},
  number = {19},
  pages = {7245--7250},
  pmid = {22529369},
  title = {{Visual attention and the acquisition of information in human crowds}},
  url = {http://www.pnas.org/cgi/doi/10.1073/pnas.1116141109},
  volume = {109},
  year = {2012}
}
@article{Lu2012,
  abstract = {Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23{\%}. Both the travel distances and size of people's movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people's movements would have become less predictable. Instead, the predictability of people's trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought.},
  author = {Lu, X. and Bengtsson, L. and Holme, P.},
  doi = {10.1073/pnas.1203882109},
  isbn = {0027-8424},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {jul},
  number = {29},
  pages = {11576--11581},
  pmid = {22711804},
  title = {{Predictability of population displacement after the 2010 Haiti earthquake}},
  url = {http://www.pnas.org/cgi/doi/10.1073/pnas.1203882109},
  volume = {109},
  year = {2012}
}
@article{Ranjan2012,
  abstract = {Call detail records (CDRs) have recently been used in studying different aspects of human mobility. While CDRs provide a means of sampling user locations at large population scales, they may not sample all locations proportionate to the visitation frequency of a user, owing to sparsity in time and space of voice--calls, thereby introducing a bias. Also, as the rate of sampling is inherently dependent on the calling frequencies of an individual, high voice--call activity users are often chosen for conducting a meaningful study. Such a selection process can, inadvertently, lead to a biased view as high frequency callers may not always be representative of an entire population. With the advent of 3G technology and wide adoption of smartphones, cellular devices have become versatile end--hosts. As the data accessed on these devices does not always require human initiation, it affords us with an unprecedented opportunity to validate the utility of CDRs for studying human mobility. In this work, we investigate various metrics for human mobility studied in literature for over a million cellular users in the San Francisco bay--area, for over a month. Our findings reveal that although the voice--call process does well to sample significant locations, such as home and work, it may in some cases incur biases in capturing the overall spatio--temporal characteristics of individual human mobility. Additionally, we motivate an "artificially" imposed sampling process, vis--a--vis the voice--call process with the same average intensity. We observe that in many cases such an imposed sampling process yields better performance results based on the usual metrics like entropies and marginal distributions used often in literature.},
  author = {Ranjan, Gyan and Zang, Hui and Zhang, Zhi-Li and Bolot, Jean},
  doi = {10.1145/2412096.2412101},
  issn = {15591662},
  journal = {ACM SIGMOBILE Mobile Computing and Communications Review},
  month = {dec},
  number = {3},
  pages = {33},
  title = {{Are call detail records biased for sampling human mobility?}},
  url = {http://dl.acm.org/citation.cfm?doid=2412096.2412101},
  volume = {16},
  year = {2012}
}
@inproceedings{Mehrotra2012,
  abstract = {We utilize disaggregated, transaction-level call records to explore differences in the communication patterns of men and women in Rwanda. Consistent with prior research, we find that in aggregate, men are significantly more active on their phones. However, by disaggregating usage by time of day and day of year, we show the male-dominated use of mobile phones is not uniform over time. Namely, while men are more active during the day, women become more active at night. We also observe striking differences in men and women's phone activity on Christmas, Valentine's Day, and on politically important days such as the Rwandan and Kenyan Election Days. This paper chronicles these differences, situating the results within the broader literature on how men and women in developing countries interact with mobile phones, as well as other information and communication technologies. Copyright 2012 ACM.},
  address = {New York, New York, USA},
  author = {Mehrotra, Anita and Nguyen, Ashley and Blumenstock, Joshua and Mohan, Viraj},
  booktitle = {Proceedings of the Fifth International Conference on Information and Communication Technologies and Development - ICTD '12},
  doi = {10.1145/2160673.2160710},
  isbn = {9781450310451},
  keywords = {CDR,Call detail records,Development,Gender,Mobile money,Mobile phones,Phone survey,Rwanda},
  pages = {297},
  publisher = {ACM Press},
  title = {{Differences in phone use between men and women}},
  url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84859055088{\&}partnerID=tZOtx3y1},
  year = {2012}
}
@inproceedings{Toole2012b,
  abstract = {Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from personal GPS devices to mobile phones are collecting massive amounts of data on urban systems. The locations, communications, and activities of millions of people are recorded and stored by new information technologies. This work utilizes novel dynamic data, generated by mobile phone users, to measure spatiotemporal changes in population. In the process, we identify the relationship between land use and dynamic population over the course of a typical week. A machine learning classification algorithm is used to identify clusters of locations with similar zoned uses and mobile phone activity patterns. It is shown that the mobile phone data is capable of delivering useful information on actual land use that supplements zoning regulations.},
  address = {New York, New York, USA},
  archiveprefix = {arXiv},
  arxivid = {1207.1115},
  author = {Toole, Jameson L. and Ulm, Michael and Bauer, Dietmar and Gonzalez, Marta C.},
  booktitle = {Proceedings of the ACM SIGKDD International Workshop on Urban Computing - UrbComp '12},
  doi = {10.1145/2346496.2346498},
  eprint = {1207.1115},
  isbn = {978-1-4503-1542-5},
  pages = {1},
  pmid = {1986018621067952938},
  publisher = {ACM Press},
  title = {{Inferring land use from mobile phone activity}},
  url = {http://arxiv.org/abs/1207.1115},
  year = {2012}
}
@article{Mervis2012,
  abstract = {A federal effort is under way to improve the nation's ability to manage, understand, and act upon the 1.2 zettabytes (1021) of electronic data generated each year. Its goal is to increase fundamental understanding of the technologies needed to manipulate and mine massive amounts of information; apply that knowledge to other scientific fields; address national goals in health, energy, defense, and education; and train more researchers to work with those technologies. The impetus for the initiative, to be managed by the Office of Science and Technology Policy, comes from a December 2010 report by a presidential task force that concluded the nation was "underinvesting" in the field. Computer scientists welcome the spotlight that the White House is shining on big-data research.},
  author = {Mervis, J.},
  doi = {10.1126/science.336.6077.22},
  isbn = {0036-8075},
  issn = {0036-8075},
  journal = {Science},
  month = {apr},
  number = {6077},
  pages = {22--22},
  pmid = {22491835},
  title = {{Agencies Rally to Tackle Big Data}},
  url = {http://www.sciencemag.org/cgi/doi/10.1126/science.336.6077.22},
  volume = {336},
  year = {2012}
}
@article{Giles2012,
  abstract = {FROM E-MAILS TO SOCIAL NETWORKS, THE DIGITAL TRACES LEFT BY LIFE IN THE MODERN WORLD ARE TRANSFORMING SOCIAL SCIENCE.},
  author = {Giles, Jim},
  doi = {10.1038/488448a},
  isbn = {0028083614764687},
  issn = {00280836},
  journal = {Nature},
  month = {aug},
  number = {7412},
  pages = {448--450},
  pmid = {22914149},
  title = {{Computational social science: Making the links}},
  url = {http://www.nature.com/doifinder/10.1038/488448a},
  volume = {488},
  year = {2012}
}
@book{Tacoli2012,
  abstract = {The majority of the world's population now live in urban centres, which will also absorb virtually all population growth in the next century. Urbanisation involves major shifts in the ways people work and live, and offers unprecedented opportunities for improved standards of living, higher life expectancy and higher literacy levels, as well as better environmental sustainability and a more efficient use of increasingly scarce natural resources. For women, urbanisation is associated with greater access to employment opportunities, lower fertility levels and increased independence. However, urbanisation does not necessarily result in a more equitable distribution of wealth and wellbeing. In many low and middle income nations, urban poverty is growing compared to rural poverty. Specific aspects differentiate urban poverty from rural poverty. While urban residents are more dependent on cash incomes to meet their essential needs, income poverty is compounded by inadequate and expensive accommodation, limited access to basic infrastructure and services, exposure to environmental hazards and high rates of crime and violence. This gives urban poverty a distinctive gendered dimension as it puts a disproportionate burden on those members of communities and households who are responsible for unpaid carework such as cleaning, cooking and looking after children, the sick and the elderly. At the same time, cash- based urban economies mean that poor women are compelled, often from a very young age, to also engage in paid activities. In many instances this involves work in the lowest-paid formal and informal sector activities which, at times of economic crises, require increasingly long hours for the same income. Combined with cuts in the public provision of services, higher costs for food, water and transport, efforts to balance paid work and unpaid carework take a growing toll on women. A gendered perspective of urban poverty reveals the significance of non-income dimensions such as time poverty. It also highlights fundamental issues of equality and social justice by showing how women's unequal position in the urban labour market, their limited ability to secure assets independently from male relatives and their greater exposure to violence},
  author = {Tacoli, Cecilia},
  booktitle = {United Nations Population Fund,London,UK},
  file = {::},
  isbn = {9781843698487},
  number = {March},
  pages = {48},
  title = {{Urbanization, gender and urban poverty: paid work and unpaid carework in the city}},
  url = {http://pubs.iied.org/10614IIED.html.},
  year = {2012}
}
@article{Dhar2013,
  abstract = {The use of the term “Data Science” is becoming increasingly common along with “Big Data.” What does Data Science mean? Is there something unique about it? What skills should a “data scientist” possess to be productive in the emerging digital age characterized by a deluge of data? What are the implications for business and for scientific inquiry? In this brief monograph I address these questions from a predictive modeling perspective.},
  author = {Dhar, Vasant},
  doi = {10.2139/ssrn.2086734},
  isbn = {0001-0782},
  issn = {00010782},
  journal = {Ssrn},
  keywords = {,data mining,data science,induction,machine learning,prediction,predictive modeling},
  month = {dec},
  number = {12},
  pages = {64--73},
  pmid = {92604156},
  publisher = {ACM},
  title = {{Data Science and Prediction}},
  url = {http://dl.acm.org/citation.cfm?doid=2534706.2500499},
  volume = {56},
  year = {2012}
}
@article{Csaji2012,
  abstract = {Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the connections between various features of human behavior extracted from a large mobile phone dataset. Our observations are based on the analysis of communication data of 100,000 anonymized and randomly chosen individuals in a dataset of communications in Portugal. We show that clustering and principal component analysis allow for a significant dimension reduction with limited loss of information. The most important features are related to geographical location. In particular, we observe that most people spend most of their time at only a few locations. With the help of clustering methods, we then robustly identify home and office locations and compare the results with official census data. Finally, we analyze the geographic spread of users' frequent locations and show that commuting distances can be reasonably well explained by a gravity model. {\textcopyright} 2012 Elsevier B.V. All rights reserved.},
  archiveprefix = {arXiv},
  arxivid = {1211.6014},
  author = {Cs{\'{a}}ji, Bal{\'{a}}zs Cs and Browet, Arnaud and Traag, V. A. and Delvenne, Jean Charles and Huens, Etienne and {Van Dooren}, Paul and Smoreda, Zbigniew and Blondel, Vincent D.},
  doi = {10.1016/j.physa.2012.11.040},
  eprint = {1211.6014},
  file = {::},
  isbn = {0378-4371},
  issn = {03784371},
  journal = {Physica A: Statistical Mechanics and its Applications},
  keywords = {Commuting distance,Data mining,Human mobility,Location detection},
  month = {nov},
  number = {6},
  pages = {1459--1473},
  title = {{Exploring the mobility of mobile phone users}},
  url = {http://arxiv.org/abs/1211.6014 http://dx.doi.org/10.1016/j.physa.2012.11.040},
  volume = {392},
  year = {2013}
}
@article{Miritello2013,
  abstract = {We used a large database of 9 billion calls from 20 million mobile users to examine the relationships between aggregated time spent on the phone, personal network size, tie strength and the way in which users distributed their limited time across their network (disparity). Compared to those with smaller networks, those with large networks did not devote proportionally more time to communication and had on average weaker ties (as measured by time spent communicating). Further, there were not substantially different levels of disparity between individuals, in that mobile users tend to distribute their time very unevenly across their network, with a large proportion of calls going to a small number of individuals. Together, these results suggest that there are time constraints which limit tie strength in large personal networks, and that even high levels of mobile communication do not fundamentally alter the disparity of time allocation across networks. {\textcopyright} 2013 Elsevier B.V.},
  archiveprefix = {arXiv},
  arxivid = {1301.2464},
  author = {Miritello, Giovanna and Moro, Esteban and Lara, Rub{\'{e}}n and Mart{\'{i}}nez-L{\'{o}}pez, Roc{\'{i}}o and Belchamber, John and Roberts, Sam G.B. and Dunbar, Robin I.M.},
  doi = {10.1016/j.socnet.2013.01.003},
  eprint = {1301.2464},
  file = {::},
  isbn = {0378-8733},
  issn = {03788733},
  journal = {Social Networks},
  keywords = {Constraints on networks,Disparity,Personal networks,Social networks,Tie strength},
  month = {jan},
  number = {1},
  pages = {89--95},
  pmid = {15734699},
  title = {{Time as a limited resource: Communication strategy in mobile phone networks}},
  url = {http://arxiv.org/abs/1301.2464},
  volume = {35},
  year = {2013}
}
@article{Gutierrez2013,
  abstract = {Reliable statistical information is important to make political decisions on a sound basis and to help measure the impact of policies. Unfortunately, statistics offices in developing countries have scarce resources and statistical censuses are therefore conducted sporadically. Based on mobile phone communications and history of airtime credit purchases, we estimate the relative income of individuals, the diversity and inequality of income, and an indicator for socioeconomic segregation for fine-grained regions of an African country. Our study shows how to use mobile phone datasets as a starting point to understand the socio-economic state of a country, which can be especially useful in countries with few resources to conduct large surveys.},
  journal = {{arXiv}},
  archiveprefix = {arXiv},
  arxivid = {1309.4496},
  author = {Gutierrez, Thoralf and Krings, Gautier and Blondel, Vincent D.},
  eprint = {1309.4496},
  file = {::},
  month = {sep},
  title = {{Evaluating socio-economic state of a country analyzing airtime credit and mobile phone datasets}},
  url = {http://arxiv.org/abs/1309.4496},
  year = {2013}
}
@article{Schneider2013,
  abstract = {Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modelling periods of high-frequency trips followed by periods of lower activity as the key ingredient.},
  author = {Schneider, Christian M. and Belik, Vitaly and Couronn{\'{e}}, Thomas and Smoreda, Zbigniew and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1098/rsif.2013.0246},
  isbn = {1742-5689$\backslash$r1742-5662},
  issn = {17425662},
  journal = {Journal of the Royal Society Interface},
  keywords = {Human dynamics,Mobile phone,Motifs,Networks},
  month = {may},
  number = {84},
  pages = {20130246--20130246},
  pmid = {23658117},
  title = {{Unravelling daily human mobility motifs}},
  url = {http://rsif.royalsocietypublishing.org/cgi/doi/10.1098/rsif.2013.0246},
  volume = {10},
  year = {2013}
}
@inproceedings{Jiang2013,
  abstract = {In this work, we present three classes of methods to extract information from triangulated mobile phone signals, and describe applications with different goals in spatiotemporal analysis and urban modeling. Our first challenge is to relate extracted information from phone records (i.e., a set of time-stamped coordinates estimated from signal strengths) with destinations by each of the million anonymous users. By demonstrating a method that converts phone signals into small grid cell destinations, we present a framework that bridges triangulated mobile phone data with previously established findings obtained from data at more coarse-grained resolutions (such as at the cell tower or census tract levels). In particular, this method allows us to relate daily mobility networks, called motifs here, with trip chains extracted from travel diary surveys. Compared with existing travel demand models mainly relying on expensive and less-frequent travel survey data, this method represents an advantage for applying ubiquitous mobile phone data to urban and transportation modeling applications. Second, we present a method that takes advantage of the high spatial resolution of the triangulated phone data to infer trip purposes by examining semantic-enriched land uses surrounding destinations in individual's motifs. In the final section, we discuss a portable computational architecture that allows us to manage and analyze mobile phone data in geospatial databases, and to map mobile phone trips onto spatial networks such that further analysis about flows and network performances can be done. The combination of these three methods demonstrate the state-of-the-art algorithms that can be adapted to triangulated mobile phone data for the context of urban computing and modeling applications. {\textcopyright} 2013 ACM.},
  address = {New York, New York, USA},
  author = {Jiang, Shan and Fiore, Gaston A. and Yang, Yingxiang and Ferreira, Joseph and Frazzoli, Emilio and Gonz{\'{a}}lez, Marta C.},
  booktitle = {Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing - UrbComp '13},
  doi = {10.1145/2505821.2505828},
  isbn = {9781450323314},
  pages = {1},
  publisher = {ACM Press},
  title = {{A review of urban computing for mobile phone traces}},
  url = {http://dl.acm.org/citation.cfm?doid=2505821.2505828},
  year = {2013}
}
@inproceedings{Schneider2013b,
  abstract = {Multi-agent models for simulating the mobility behavior of the urban population are gaining momentum due to increasing computing power. Such models pose high demands in terms of input data in order to be reliably able to match real world behavior. To run the models a synthetic population mirroring typical mobility demand needs to be generated based on real world observations. Traditionally this is done using travel diary surveys, which are costly (and hence have relatively low sample size) and focus mainly on trip choice rather than on activities for an entire day. Thus in this setting the generation of synthetic populations either relies on resampling identical activity chains or on imposing independence of various trips occurring during the day. Both assumptions are not realistic. Using Call Detail Records (CDRs) it has been found that individual daily movement uses only a small number of movement patterns. These patterns, termed motifs, appear stably in many different cities, as has been shown for both CDR data as well as travel diaries. In this paper the relation between these motifs and other mobility related quantities like the distribution of travel distances and times as well as mode choice is investigated. Additionally transition probabilities both for motifs (relevant for multi-day simulations) and mode transitions are discussed. The main finding is that while some of the characteristics seem to be unrelated to motifs, others such as mode choice exhibit strong correlations which could improve the provision of synthetic populations for multi-agent models. Thus the results in this paper are seen as one step further towards the creation of realistic (with respect to mobility behavior) synthetic populations for multi-agent models in order to analyze the performance of multi-modal transportation systems or disease spreading in urban areas. {\textcopyright} 2013 ACM.},
  address = {New York, New York, USA},
  author = {Schneider, Christian M. and Rudloff, Christian and Bauer, Dietmar and Gonz{\'{a}}lez, Marta C.},
  booktitle = {Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing - UrbComp '13},
  doi = {10.1145/2505821.2505829},
  isbn = {9781450323314},
  keywords = {demand modeling,human mobility,mobility,motifs,multi-agent models},
  pages = {1},
  publisher = {ACM Press},
  title = {{Daily travel behavior}},
  url = {http://dl.acm.org/citation.cfm?id=2505829{\%}5Cnhttp://dl.acm.org/citation.cfm?doid=2505821.2505829},
  year = {2013}
}
@book{IEEEComputerSociety,
  abstract = {"IEEE Computer Society Order Number E5046"--Copyright page.},
  author = {{IEEE Computer Society} and {Institute of Electrical and Electronics Engineers} and {IEEE International Conference on Internet of Things (2013 : Beijing}, China) and {IEEE International Conference on Cyber}, Physical and Social Computing (2013 : Beijing},
  booktitle = {Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013},
  isbn = {9780769550466},
  title = {{Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013}},
  url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84893459002{\&}partnerID=tZOtx3y1},
  year = {2013}
}
@inproceedings{Xiang2013,
  abstract = {The ubiquitous mobile technology has enabled the sense of massive information of the mega population in urban areas through an efficient way. Deep analysis of huge CDR (Call Detail Record) data can help to uncover the pattern and nature of the human mobility or city dynamics. In this paper, we conduct our experiments with trajectories of millions of mobile phone subscribers. Through the exploration of the spatial pattern of caller, we study the call flow between two consecutive places where the phone call event happens and discover calling habits in most phone users. The result of our experiment reveals that the barriers or gaps of mobile communication do exist in urban city and it fits well with the landscape. It is shown that mobile call record can support and complement a wide range of studies from urban planning to traffic management.},
  author = {Xiang, Feng and Tu, Lai and Huang, Benxiong},
  booktitle = {Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013},
  doi = {10.1109/GreenCom-iThings-CPSCom.2013.149},
  isbn = {9780769550466},
  keywords = {CDR,Dynamic City,Human Mobility},
  month = {aug},
  pages = {850--855},
  publisher = {IEEE},
  title = {{Inferring barriers of urban city using mobile phone record}},
  url = {http://ieeexplore.ieee.org/document/6682163/},
  year = {2013}
}
@article{Mock2013,
  abstract = {Food and Nutrition Security Information (FNSI) is a critical tool for achieving food and nutrition security, yet FNSI efforts to date have not produced the intended impacts on policy and program decision making, largely due to shortcomings in available technologies and frameworks. The article reviews the evolution of FNSI efforts in the context of emerging technology and data collection techniques. A conceptual framework is provided to describe the evolution towards an FNSI characterized by integrating conventional and novel approaches to the collection, analysis and communication of information into a value stream that supports decision-making to achieve food security. Conclusions include the need to streamline and expand coverage of conventional information tools such as household surveys while facilitating the rapid uptake of analytical tools that leverage the novel, numerous, and rich data streams enabled by emergent information and communication technologies and dramatic increases in connectivity. {\textcopyright} 2012 Elsevier B.V.},
  author = {Mock, Nancy and Morrow, Nathan and Papendieck, Adam},
  doi = {10.1016/j.gfs.2012.11.007},
  isbn = {2211-9124},
  issn = {22119124},
  journal = {Global Food Security},
  keywords = {Complex adaptive systems,Conceptual framework,Food and nutrition security,Information systems},
  month = {mar},
  number = {1},
  pages = {41--49},
  title = {{From complexity to food security decision-support: Novel methods of assessment and their role in enhancing the timeliness and relevance of food and nutrition security information}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S2211912412000351},
  volume = {2},
  year = {2013}
}
@article{Becker2013,
  abstract = {Characterizing human mobility patterns is critical to a deeper understanding of the effects of people's travel on society and the environment. Location information from cellular tele- phone networks can shed light on humanmovements cheaply, frequently, and on a large scale. We have developed tech- niques for analyzing anonymous cellphone locations to ex- plore various aspects of human mobility. In particular, we have analyzed billions of location samples for hundreds of thousands of people in each of the Los Angeles, San Fran- cisco, and New York metropolitan areas. Our results include measures of how far people travel every day, estimates of carbon footprints due to home-to-work commutes, density maps of the residential areas that contribute workers to a city, and relative traffic volumes on commuting routes. We have validated our techniques through comparisons against ground truth provided by volunteers, and against indepen- dent sources such as the US Census Bureau. Throughout our work, we have taken measures to preserve the privacy of cellphone users. This article presents an overview of our methodologies and findings. 1.},
  author = {Becker, Richard and Volinsky, Chris and C{\'{a}}ceres, Ram{\'{o}}n and Hanson, Karrie and Isaacman, Sibren and Loh, Ji Meng and Martonosi, Margaret and Rowland, James and Urbanek, Simon and Varshavsky, Alexander},
  doi = {10.1145/2398356.2398375},
  isbn = {9788476586037},
  issn = {00010782},
  journal = {Communications of the ACM},
  month = {jan},
  number = {1},
  pages = {74},
  title = {{Human mobility characterization from cellular network data}},
  url = {http://dl.acm.org/citation.cfm?doid=2398356.2398375},
  volume = {56},
  year = {2013}
}
@article{Overeem2013,
  abstract = {Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km(2)), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent.},
  author = {Overeem, A. and Leijnse, H. and Uijlenhoet, R.},
  doi = {10.1073/pnas.1217961110},
  isbn = {1091-6490 (Electronic)$\backslash$r0027-8424 (Linking)},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {feb},
  number = {8},
  pages = {2741--2745},
  pmid = {23382210},
  title = {{Country-wide rainfall maps from cellular communication networks}},
  url = {http://www.pnas.org/cgi/doi/10.1073/pnas.1217961110},
  volume = {110},
  year = {2013}
}
@inproceedings{Moumni2013,
  abstract = {The data generated by pervasive infrastructures, and specially cell-phone networks, has been used in the past to improve responses to emergency events such as natural disasters or disease outbreaks. However, very little work has focused on analyzing the social response to an urban earthquake as it takes place. In this paper we present a preliminary study of the social response using the information collected from a cell-phone network during the 2012 Oaxaca earthquake in Mexico. We focus our analysis on four urban environments located between 100-200km away from the epicenter of the earthquake. The social response is analyzed using four different variables: call volume, call duration, social activity and mobility. Initial results indicate a social response characterized by an increase in the number of calls, a decrease in call durations, a moderate increase in the number of people contacted by highly connected citizens and a moderate increase in the mobility. Copyright {\textcopyright} 2013 ACM.},
  address = {New York, New York, USA},
  author = {Moumni, Benyounes and Frias-Martinez, Vanessa and Frias-Martinez, Enrique},
  booktitle = {Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication - UbiComp '13 Adjunct},
  doi = {10.1145/2494091.2497350},
  isbn = {9781450322157},
  pages = {1199--1208},
  publisher = {ACM Press},
  title = {{Characterizing social response to urban earthquakes using cell-phone network data}},
  url = {http://dl.acm.org/citation.cfm?doid=2494091.2497350},
  year = {2013}
}
@article{Wesolowski2013,
  abstract = {Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.},
  author = {Wesolowski, Amy and Buckee, Caroline O. and Pindolia, Deepa K. and Eagle, Nathan and Smith, David L. and Garcia, Andres J. and Tatem, Andrew J.},
  doi = {10.1371/journal.pone.0052971},
  editor = {Hart, John P.},
  isbn = {1932-6203 (Electronic)
1932-6203 (Linking)},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {jan},
  number = {1},
  pages = {e52971},
  pmid = {23326367},
  title = {{The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales}},
  url = {http://dx.plos.org/10.1371/journal.pone.0052971},
  volume = {8},
  year = {2013}
}
@article{Calabrese2013,
  abstract = {Large-scale urban sensing data such as mobile phone traces are emerging as an important data source for urban modeling. This study represents a first step towards building a methodology whereby mobile phone data can be more usefully applied to transportation research. In this paper, we present techniques to extract useful mobility information from the mobile phone traces of millions of users to investigate individual mobility patterns within a metropolitan area. The mobile-phone-based mobility measures are compared to mobility measures computed using odometer readings from the annual safety inspections of all private vehicles in the region to check the validity of mobile phone data in characterizing individual mobility and to identify the differences between individual mobility and vehicular mobility. The empirical results can help us understand the intra-urban variation of mobility and the non-vehicular component of overall mobility. More importantly, this study suggests that mobile phone trace data represent a reasonable proxy for individual mobility and show enormous potential as an alternative and more frequently updatable data source and a compliment to the conventional travel surveys in mobility study. {\textcopyright} 2012 Elsevier Ltd.},
  author = {Calabrese, Francesco and Diao, Mi and {Di Lorenzo}, Giusy and Ferreira, Joseph and Ratti, Carlo},
  doi = {10.1016/j.trc.2012.09.009},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {Mobile phone traces,Mobility analysis,Vehicle Kilometers Traveled (VKT)},
  month = {jan},
  pages = {301--313},
  title = {{Understanding individual mobility patterns from urban sensing data: A mobile phone trace example}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X12001192},
  volume = {26},
  year = {2013}
}
@article{DeMontjoye2013,
  abstract = {We study fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95{\%} of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resolution and the available outside information. This formula shows that the uniqueness of mobility traces decays approximately as the 1/10 power of their resolution. Hence, even coarse datasets provide little anonymity. These findings represent fundamental constraints to an individual's privacy and have important implications for the design of frameworks and institutions dedicated to protect the privacy of individuals.},
  author = {{De Montjoye}, Yves Alexandre and Hidalgo, C{\'{e}}sar A. and Verleysen, Michel and Blondel, Vincent D.},
  doi = {10.1038/srep01376},
  isbn = {2045-2322 (Electronic)$\backslash$r2045-2322 (Linking)},
  issn = {20452322},
  journal = {Scientific Reports},
  keywords = {Applied mathematics,Applied physics,Computational science,Statistics},
  month = {dec},
  number = {1},
  pages = {1376},
  pmid = {23524645},
  publisher = {Nature Publishing Group},
  title = {{Unique in the Crowd: The privacy bounds of human mobility}},
  url = {http://www.nature.com/articles/srep01376},
  volume = {3},
  year = {2013}
}
@article{Zhong2013,
  abstract = {Demographics prediction is an important component of user profile modeling. The accurate prediction of users' demographics can help promote many applications, ranging from web search, personalization to behavior targeting. In this paper, we focus on how to predict users' demographics, including "gender", "job type", "marital status", "age" and "number of family members", based on mobile data, such as users' usage logs, physical activities and environmental contexts. The core idea is to build a supervised learning framework, where each user is represented as a feature vector and users' demographics are considered as prediction targets. The most important component is to construct features from raw data and then supervised learning models can be applied. We propose a feature construction framework, CFC (contextual feature construction), where each feature is defined as the conditional probability of one user activity under the given contexts. Consequently, besides employing standard supervised learning models, we propose a regularized multi-task learning framework to model different kinds of demographics predictions collectively. We also propose a cost-sensitive classification framework for regression tasks, in order to benefit from the existing dimension reduction methods. Finally, due to the limited training instances, we employ ensemble to avoid overfitting. The experimental results show that the framework achieves classification accuracies on "gender", "job" and "marital status" as high as 96{\%}, 83{\%} and 86{\%}, respectively, and achieves Root Mean Square Error (RMSE) on "age" and "number of family members" as low as 0.69 and 0.66 respectively, under the leave-one-out evaluation. {\textcopyright} 2013 Elsevier B.V. All rights reserved.},
  author = {Zhong, Erheng and Tan, Ben and Mo, Kaixiang and Yang, Qiang},
  doi = {10.1016/j.pmcj.2013.07.009},
  issn = {15741192},
  journal = {Pervasive and Mobile Computing},
  keywords = {Cost-sensitive classification,Demographics,Ensemble,Feature construction,Mobile,Multi-task learning},
  month = {dec},
  number = {6},
  pages = {823--837},
  title = {{User demographics prediction based on mobile data}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1574119213000916},
  volume = {9},
  year = {2013}
}
@article{Krumme2013,
  abstract = {We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. Yet while aggregate behavior is largely predictable, the interleaving of shopping events introduces important stochastic elements at short time scales. These short- and long-scale patterns suggest a theoretical upper bound on predictability, and describe the accuracy of a Markov model in predicting a person's next location. We incorporate population-level transition probabilities in the predictive models, and find that in many cases these improve accuracy. While our results point to the elusiveness of precise predictions about where a person will go next, they suggest the existence, at large time-scales, of regularities across the population.},
  archiveprefix = {arXiv},
  arxivid = {1008.2556},
  author = {Krumme, Coco and Llorente, Alejandro and Cebrian, Manuel and Pentland, Alex and Moro, Esteban},
  doi = {10.1038/srep01645},
  eprint = {1008.2556},
  isbn = {2045-2322 (Electronic)$\backslash$r2045-2322 (Linking)},
  issn = {20452322},
  journal = {Scientific Reports},
  month = {dec},
  number = {1},
  pages = {1645},
  pmid = {23598917},
  title = {{The predictability of consumer visitation patterns}},
  url = {http://www.nature.com/articles/srep01645},
  volume = {3},
  year = {2013}
}
@article{SandyPentland2013,
  abstract = {The digital traces we leave behind each day reveal more about$\backslash$nus than we know. This could become a privacy nightmare—or it could$\backslash$nbe the foundation of a healthier, more prosperous world},
  author = {Pentland, Alex},
  doi = {10.1038/scientificamerican1013-78},
  isbn = {0036-8733},
  issn = {00368733},
  journal = {Scientific American},
  month = {sep},
  number = {4},
  pages = {78--83},
  pmid = {24137860},
  title = {{The data-driven society}},
  url = {http://www.nature.com/doifinder/10.1038/scientificamerican1013-78},
  volume = {309},
  year = {2013}
}
@article{Hill2013,
  abstract = {Opt-in surveys are the most widespread method used to study participation in online communities, but produce biased results in the absence of adjustments for non-response. A 2008 survey conducted by the Wikimedia Foundation and United Nations University at Maastricht is the source of a frequently cited statistic that less than 13{\%} of Wikipedia contributors are female. However, the same study suggested that only 39.9{\%} of Wikipedia readers in the US were female - a finding contradicted by a representative survey of American adults by the Pew Research Center conducted less than two months later. Combining these two datasets through an application and extension of a propensity score estimation technique used to model survey non-response bias, we construct revised estimates, contingent on explicit assumptions, for several of the Wikimedia Foundation and United Nations University at Maastricht claims about Wikipedia editors. We estimate that the proportion of female US adult editors was 27.5{\%} higher than the original study reported (22.7{\%}, versus 17.8{\%}), and that the total proportion of female editors was 26.8{\%} higher (16.1{\%}, versus 12.7{\%}).},
  author = {Hill, Benjamin Mako and Shaw, Aaron},
  doi = {10.1371/journal.pone.0065782},
  editor = {S{\'{a}}nchez, Angel},
  file = {::},
  isbn = {1932-6203},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {jun},
  number = {6},
  pages = {e65782},
  pmid = {23840366},
  publisher = {Public Library of Science},
  title = {{The Wikipedia Gender Gap Revisited: Characterizing Survey Response Bias with Propensity Score Estimation}},
  url = {http://dx.plos.org/10.1371/journal.pone.0065782},
  volume = {8},
  year = {2013}
}
@inproceedings{Wang2013,
  address = {New York, New York, USA},
  author = {Wang, Yi-Chia and Burke, Moira and Kraut, Robert E.},
  booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI '13},
  doi = {10.1145/2470654.2470659},
  isbn = {9781450318990},
  keywords = {computer-mediated communication,facebook,gender,natural language analysis,social networking sites,topics},
  pages = {31},
  publisher = {ACM Press},
  title = {{Gender, topic, and audience response}},
  url = {http://dl.acm.org/citation.cfm?doid=2470654.2470659},
  year = {2013}
}
@article{Wu2013,
  abstract = {The increasing ubiquity of smartphones coupled with the mobility of their users will allow the use of smartphones to enhance the operation of wireless sensor networks. In addition to accessing data from a wireless sensor network for personal use, and the generation of data through participatory sensing, we propose the use of smartphones to collect data from sensor nodes opportunistically. For this to be feasible, the mobility patterns of smartphone users must support opportunistic use. We analyze the dataset from the Mobile Data Challenge by Nokia, and we identify the significant patterns, including strong spatial and temporal localities. These patterns should be exploited when designing protocols and algorithms, and their existence supports the proposal for opportunistic data collection through smartphones. {\textcopyright} 2013 Elsevier B.V. All rights reserved.},
  author = {Wu, Xiuchao and Brown, Kenneth N. and Sreenan, Cormac J.},
  doi = {10.1016/j.pmcj.2013.07.003},
  issn = {15741192},
  journal = {Pervasive and Mobile Computing},
  keywords = {Human mobility,Opportunistic data collection,Smartphone,Wireless sensor network},
  month = {dec},
  number = {6},
  pages = {881--891},
  title = {{Analysis of smartphone user mobility traces for opportunistic data collection in wireless sensor networks}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1574119213000850},
  volume = {9},
  year = {2013}
}
@article{Liu2013,
  abstract = {Individual human travel patterns captured by mobile phone data have been quantitatively characterized by mathematical models, but the underlying activities which initiate the movement are still in a less-explored stage. As a result of the nature of how activity and related travel decisions are made in daily life, human activity-travel behavior exhibits a high degree of spatial and temporal regularities as well as sequential ordering. In this study, we investigate to what extent the behavioral routines could reveal the activities being performed at mobile phone call locations that are captured when users initiate or receive a voice call or message. Our exploration consists of four steps. First, we define a set of comprehensive temporal variables characterizing each call location. Feature selection techniques are then applied to choose the most effective variables in the second step. Next, a set of state-of-the-art machine learning algorithms including Support Vector Machines, Logistic Regression, Decision Trees and Random Forests are employed to build classification models. Alongside, an ensemble of the results of the above models is also tested. Finally, the inference performance is further enhanced by a post-processing algorithm. Using data collected from natural mobile phone communication patterns of 80 users over a period of more than one year, we evaluated our approach via a set of extensive experiments. Based on the ensemble of the models, we achieved prediction accuracy of 69.7{\%}. Furthermore, using the post processing algorithm, the performance obtained a 7.6{\%} improvement. The experiment results demonstrate the potential to annotate mobile phone locations based on the integration of data mining techniques with the characteristics of underlying activity-travel behavior, contributing towards the semantic comprehension and further application of the massive data. {\textcopyright} 2013 Elsevier B.V. All rights reserved.},
  author = {Liu, Feng and Janssens, Davy and Wets, Geert and Cools, Mario},
  doi = {10.1016/j.eswa.2012.12.100},
  isbn = {0957-4174},
  issn = {09574174},
  journal = {Expert Systems with Applications},
  keywords = {Activity-travel behavior,Feature selection techniques,Machine learning algorithms,Mobile phone location annotation,Sequential information},
  month = {jun},
  number = {8},
  pages = {3299--3311},
  title = {{Annotating mobile phone location data with activity purposes using machine learning algorithms}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0957417412013425},
  volume = {40},
  year = {2013}
}
@article{Wesolowski2014,
  abstract = {The ongoing Ebola outbreak is taking place in one of the most highly connected and densely populated regions of Africa (Figure 1A). Accurate information on population movements is valuable for monitoring the progression of the outbreak and predicting its future spread, facilitating the prioritization of interventions and designing surveillance and containment strategies. Vital questions include how the affected regions are connected by population flows, which areas are major mobility hubs, what types of movement typologies exist in the region, and how all of these factors are changing as people react to the outbreak and movement restrictions are put in place. Just a decade ago, obtaining detailed and comprehensive data to answer such questions over this huge region would have been impossible. Today, such valuable data exist and are collected in real?time, but largely remain unused for public health purposes – stored on the servers of mobile phone operators. In this commentary, we outline the utility of CDRs for understanding human mobility in the context of the Ebola, and highlight the need to develop protocols for rapid sharing of operator data in response to public health emergencies. http://currents.plos.org/outbreaks/article/containing-the-ebola-outbreak-th},
  author = {Wesolowski, Amy and Buckee, Caroline O. and Bengtsson, Linus and Wetter, Erik and Lu, Xin and Tatem, Andrew J.},
  doi = {10.1371/currents.outbreaks.0177e7fcf52217b8b634376e2f3efc5e},
  isbn = {2157-3999 (Electronic)},
  issn = {2157-3999},
  journal = {PLoS Currents},
  keywords = {cellphone,disease model,disease outbreak,ebola,mobility,travel},
  month = {sep},
  pmid = {25642369},
  title = {{Commentary: Containing the Ebola Outbreak - the Potential and Challenge of Mobile Network Data}},
  url = {http://currents.plos.org/outbreaks/article/containing-the-ebola-outbreak-the-potential-and-challenge-of-mobile-network-data/},
  volume = {6},
  year = {2014}
}
@article{Deville2014,
  abstract = {During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotem- poral distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estima- tions of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also dem- onstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applica- tions and a near real-time understanding of patterns and pro- cesses in human geography.},
  author = {Deville, Pierre and Linard, Catherine and Martin, Samuel and Gilbert, Marius and Stevens, Forrest R. and Gaughan, Andrea E. and Blondel, Vincent D. and Tatem, Andrew J.},
  doi = {10.1073/pnas.1408439111},
  isbn = {0027-8424, 1091-6490},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  keywords = {census,human mobility,phone calls,population distribution,remote sensing},
  month = {nov},
  number = {45},
  pages = {15888--15893},
  pmid = {25349388},
  title = {{Dynamic population mapping using mobile phone data}},
  url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1408439111},
  volume = {111},
  year = {2014}
}
@article{Pei2013,
  abstract = {Land-use classification is essential for urban planning. Urban land-use types can be differentiated either by their physical characteristics (such as reflectivity and texture) or social functions. Remote sensing techniques have been recognized as a vital method for urban land-use classification because of their ability to capture the physical characteristics of land use. Although significant progress has been achieved in remote sensing methods designed for urban land-use classification, most techniques focus on physical characteristics, whereas knowledge of social functions is not adequately used. Owing to the wide usage of mobile phones, the activities of residents, which can be retrieved from the mobile phone data, can be determined in order to indicate the social function of land use. This could bring about the opportunity to derive land-use information from mobile phone data. To verify the application of this new data source to urban land-use classification, we first construct a vector of aggregated mobile phone data to characterize land-use types. This vector is composed of two aspects: the normalized hourly call volume and the total call volume. A semi-supervised fuzzy c-means clustering approach is then applied to infer the land-use types. The method is validated using mobile phone data collected in Singapore. Land use is determined with a detection rate of 58.03{\%}. An analysis of the land-use classification results shows that the detection rate decreases as the heterogeneity of land use increases, and increases as the density of cell phone towers increases.},
  archiveprefix = {arXiv},
  arxivid = {1310.6129},
  author = {Pei, Tao and Sobolevsky, Stanislav and Ratti, Carlo and Shaw, Shih-Lung and Li, Ting and Zhou, Chenghu},
  doi = {10.1080/13658816.2014.913794},
  eprint = {1310.6129},
  file = {::},
  isbn = {1365-8816},
  issn = {1365-8816},
  journal = {International Journal of Geographical Information Science},
  month = {oct},
  number = {9},
  pages = {1988--2007},
  title = {{A new insight into land use classification based on aggregated mobile phone data}},
  url = {http://www.tandfonline.com/doi/abs/10.1080/13658816.2014.913794},
  volume = {28},
  year = {2014}
}
@article{Kung2013,
  abstract = {Home-work commuting has always attracted significant research attention because of its impact on human mobility. One of the key assumptions in this domain of study is the universal uniformity of commute times. However, a true comparison of commute patterns has often been hindered by the intrinsic differences in data collection methods, which make observation from different countries potentially biased and unreliable. In the present work, we approach this problem through the use of mobile phone call detail records (CDRs), which offers a consistent method for investigating mobility patterns in wholly different parts of the world. We apply our analysis to a broad range of datasets, at both the country (Portugal, Ivory Coast, and Saudi Arabia), and city (Boston) scale. Additionally, we compare these results with those obtained from vehicle GPS traces in Milan. While different regions have some unique commute time characteristics, we show that the home-work time distributions and average values within a single region are indeed largely independent of commute distance or country (Portugal, Ivory Coast, and Boston)-despite substantial spatial and infrastructural differences. Furthermore, our comparative analysis demonstrates that such distance-independence holds true only if we consider multimodal commute behaviors-as consistent with previous studies. In car-only (Milan GPS traces) and car-heavy (Saudi Arabia) commute datasets, we see that commute time is indeed influenced by commute distance. Finally, we put forth a testable hypothesis and suggest ways for future work to make more accurate and generalizable statements about human commute behaviors.},
  archiveprefix = {arXiv},
  arxivid = {1311.2911},
  author = {Kung, Kevin S. and Greco, Kael and Sobolevsky, Stanislav and Ratti, Carlo},
  doi = {10.1371/journal.pone.0096180},
  eprint = {1311.2911},
  file = {::},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {nov},
  number = {6},
  pmid = {24933264},
  title = {{Exploring universal patterns in human home-work commuting from mobile phone data}},
  url = {http://arxiv.org/abs/1311.2911 http://dx.doi.org/10.1371/journal.pone.0096180},
  volume = {9},
  year = {2014}
}
@article{Ferrara2014,
  abstract = {The study of criminal networks using traces from heterogeneous communication media is acquiring increasing importance in nowadays society. The usage of communication media such as mobile phones and online social networks leaves digital traces in the form of metadata that can be used for this type of analysis. The goal of this work is twofold: first we provide a theoretical framework for the problem of detecting and characterizing criminal organizations in networks reconstructed from phone call records. Then, we introduce an expert system to support law enforcement agencies in the task of unveiling the underlying structure of criminal networks hidden in communication data. This platform allows for statistical network analysis, community detection and visual exploration of mobile phone network data. It enables forensic investigators to deeply understand hierarchies within criminal organizations, discovering members who play central role and provide connection among sub-groups. Our work concludes illustrating the adoption of our computational framework for a real-word criminal investigation. {\textcopyright} 2014 Elsevier Ltd. All rights reserved.},
  archiveprefix = {arXiv},
  arxivid = {1404.1295},
  author = {Ferrara, Emilio and {De Meo}, Pasquale and Catanese, Salvatore and Fiumara, Giacomo},
  doi = {10.1016/j.eswa.2014.03.024},
  eprint = {1404.1295},
  file = {::},
  isbn = {0957-4174},
  issn = {09574174},
  journal = {Expert Systems with Applications},
  keywords = {Community detection,Criminal communities,Criminal networks},
  month = {apr},
  number = {13},
  pages = {5733--5750},
  title = {{Detecting criminal organizations in mobile phone networks}},
  url = {http://arxiv.org/abs/1404.1295 http://dx.doi.org/10.1016/j.eswa.2014.03.024},
  volume = {41},
  year = {2014}
}
@article{Ferrara2014a,
  abstract = {In the fight against the racketeering and terrorism, knowledge about the structure and the organization of criminal networks is of fundamental importance for both the investigations and the development of efficient strategies to prevent and restrain crimes. Intelligence agencies exploit information obtained from the analysis of large amounts of heterogeneous data deriving from various informative sources including the records of phone traffic, the social networks, surveillance data, interview data, experiential police data, and police intelligence files, to acquire knowledge about criminal networks and initiate accurate and destabilizing actions. In this context, visual representation techniques coordinate the exploration of the structure of the network together with the metrics of social network analysis. Nevertheless, the utility of visualization tools may become limited when the dimension and the complexity of the system under analysis grow beyond certain terms. In this paper we show how we employ some interactive visualization techniques to represent criminal and terrorist networks reconstructed from phone traffic data, namely foci, fisheye and geo-mapping network layouts. These methods allow the exploration of the network through animated transitions among visualization models and local enlargement techniques in order to improve the comprehension of interesting areas. By combining the features of the various visualization models it is possible to gain substantial enhancements with respect to classic visualization models, often unreadable in those cases of great complexity of the network.},
  archiveprefix = {arXiv},
  arxivid = {1407.2837},
  author = {Ferrara, Emilio and {De Meo}, Pasquale and Catanese, Salvatore and Fiumara, Giacomo},
  eprint = {1407.2837},
  file = {::},
  issn = {16130073},
  journal = {CEUR Workshop Proceedings},
  keywords = {Criminal networks,Mobile phone networks,Visualization},
  month = {jul},
  title = {{Visualizing criminal networks reconstructed from mobile phone records}},
  url = {http://arxiv.org/abs/1407.2837},
  volume = {1210},
  year = {2014}
}
@article{Pastor-Escuredo2014,
  abstract = {Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.},
  archiveprefix = {arXiv},
  arxivid = {1411.6574},
  author = {Pastor-Escuredo, David and Morales-Guzm{\'{a}}n, Alfredo and Torres-Fern{\'{a}}ndez, Yolanda and Bauer, Jean Martin and Wadhwa, Amit and Castro-Correa, Carlos and Romanoff, Liudmyla and Lee, Jong Gun and Rutherford, Alex and Frias-Martinez, Vanessa and Oliver, Nuria and Frias-Martinez, Enrique and Luengo-Oroz, Miguel},
  doi = {10.1109/GHTC.2014.6970293},
  eprint = {1411.6574},
  file = {::},
  isbn = {9781479971930},
  journal = {Proceedings of the 4th IEEE Global Humanitarian Technology Conference, GHTC 2014},
  keywords = {Big Data for Development,Emergency Service Allocation,Human Behavior Modeling,Mobile Data Analysis,Natural Disaster Response},
  month = {nov},
  pages = {279--286},
  title = {{Flooding through the lens of mobile phone activity}},
  url = {http://arxiv.org/abs/1411.6574 http://dx.doi.org/10.1109/GHTC.2014.6970293},
  year = {2014}
}
@article{Decuyper2014,
  abstract = {Recent studies have shown the value of mobile phone data to tackle problems related to economic development and humanitarian action. In this research, we assess the suitability of indicators derived from mobile phone data as a proxy for food security indicators. We compare the measures extracted from call detail records and airtime credit purchases to the results of a nationwide household survey conducted at the same time. Results show high correlations ({\textgreater} .8) between mobile phone data derived indicators and several relevant food security variables such as expenditure on food or vegetable consumption. This correspondence suggests that, in the future, proxies derived from mobile phone data could be used to provide valuable up-to-date operational information on food security throughout low and middle income countries.},
  archiveprefix = {arXiv},
  arxivid = {1412.2595},
  author = {Decuyper, Adeline and Rutherford, Alex and Wadhwa, Amit and Bauer, Jean-Martin and Krings, Gautier and Gutierrez, Thoralf and Blondel, Vincent D. and Luengo-Oroz, Miguel A.},
  eprint = {1412.2595},
  file = {::},
  month = {nov},
  title = {{Estimating Food Consumption and Poverty Indices with Mobile Phone Data}},
  url = {http://arxiv.org/abs/1412.2595},
  year = {2014}
}
@techreport{Sarraute2015,
  abstract = {Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We were able to detect significant differences in phone usage among different subgroups of the population. Our second contribution is to provide a novel methodology to predict demographic features (namely age and gender) of unlabeled users by leveraging individual calling patterns, as well as the structure of the communication graph. We provide details of the methodology and show experimental results on a real world dataset that involves millions of users.},
  institution = {arXiv},
  number = {1511.06656},
  author = {Sarraute, Carlos and Blanc, Pablo and Burroni, Javier},
  booktitle = {Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on},
  doi = {10.1109/ASONAM.2014.6921683},
  eprint = {1511.06656},
  file = {::},
  isbn = {VO -},
  keywords = {Algorithm design and analysis,Machine learning algorithms,Mexican mobile phone users,Mexico,Mobile handsets,Prediction algorithms,Social network services,Sociology,Statistics,communication graph,individual calling patterns,mobile computing,mobile phone usage patterns,real world dataset},
  month = {nov},
  pages = {836--843},
  title = {{A study of age and gender seen through mobile phone usage patterns in Mexico}},
  url = {http://ieeexplore.ieee.org/document/6921683/},
  year = {2014}
}
@article{Jarv2014,
  abstract = {Human activity-travel behaviour (ATB) is a complex pattern of paths and activities in space and time. Studies indicate that ATB is the construction of daily habitual, weekly, monthly and seasonal routines together with strong variety seeking behaviour. Daily habitual travel patterns are usually taken as a basis, but for transportation planners more knowledge is needed on longitudinal trends in human ATB. Empirical data on prolonged perspective are hard to come by while mobile phone based call detail records could be one means of narrowing this research gap. By implementing this method, the present study attempts to provide new insights on individual monthly spatial travel behaviour. Using call detail records obtained from a set of anonymous mobile phone users, we examined their activity locations and activity spaces for 12 consecutive months. We found modest monthly variation in the number of activity locations, whereas there were great variations in the sizes of individual activity spaces. The monthly variation in individual spatial behaviour is explained up to 17{\%} by seasonality, although the variance is predominantly attributed to individual factors and results indicate significant intrapersonal monthly variability. Findings suggest new avenues for future work on ATB from a longitudinal perspective. {\textcopyright} 2013 Elsevier Ltd.},
  author = {J{\"{a}}rv, Olle and Ahas, Rein and Witlox, Frank},
  doi = {10.1016/j.trc.2013.11.003},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {Activity space,Estonia,Longitudinal data,Mobile phone data,Monthly variability,Spatial behaviour},
  month = {jan},
  pages = {122--135},
  title = {{Understanding monthly variability in human activity spaces: A twelve-month study using mobile phone call detail records}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X13002301},
  volume = {38},
  year = {2014}
}
@article{Iqbal2014,
  abstract = {In this research, we propose a methodology to develop OD matrices using mobile phone Call Detail Records (CDR) and limited traffic counts. CDR, which consist of time stamped tower locations with caller IDs, are analyzed first and trips occurring within certain time windows are used to generate tower-to-tower transient OD matrices for different time periods. These are then associated with corresponding nodes of the traffic network and converted to node-to-node transient OD matrices. The actual OD matrices are derived by scaling up these node-to-node transient OD matrices. An optimization based approach, in conjunction with a microscopic traffic simulation platform, is used to determine the scaling factors that result best matches with the observed traffic counts. The methodology is demonstrated using CDR from 2.87 million users of Dhaka, Bangladesh over a month and traffic counts from 13 key locations over 3. days of that month. The applicability of the methodology is supported by a validation study. {\textcopyright} 2014 Elsevier Ltd.},
  author = {Iqbal, Md Shahadat and Choudhury, Charisma F. and Wang, Pu and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1016/j.trc.2014.01.002},
  isbn = {0968090X},
  issn = {0968090X},
  journal = {Transportation Res. Part C: Emerging Technologies},
  keywords = {Mobile phone,Origin-destination,Traffic microsimulation,Video count},
  pages = {63--74},
  title = {{Development of origin-destination matrices using mobile phone call data}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X14000059},
  volume = {40},
  year = {2014}
}
@article{Xiong2014,
  abstract = {Mobile applications and services relying on mobility prediction have recently spurred lots of interest. In this paper, we propose mobility prediction based on cellular traces as an infrastructural level service of telecom cloud. Mobility Prediction as a Service (MPaaS) embeds mobility mining and forecasting algorithms into a cloud-based user location tracking framework. By empowering MPaaS, the hosted 3rd-party and value-added services can benefit from online mobility prediction. Particularly we took Mobility-aware Personalization and Predictive Resource Allocation as key features to elaborate how MPaaS drives new fashion of mobile cloud applications. Due to the randomness of human mobility patterns, mobility predicting remains a very challenging task in MPaaS research. Our preliminary study observed collective behavioral patterns (CBP) in mobility of crowds, and proposed a CBP-based mobility predictor. MPaaS system equips a hybrid predictor fusing both CBP-based scheme and Markov-based predictor to provide telecom cloud with large-scale mobility prediction capacity.},
  author = {Xiong, Haoyi and Zhang, Daqing and Zhang, Daqiang and Gauthier, Vincent and Yang, Kun and Becker, Monique},
  doi = {10.1007/s10796-013-9476-z},
  isbn = {1387-3326},
  issn = {13873326},
  journal = {Information Systems Frontiers},
  keywords = {Collective behaviors,Mobile cloud computing,Mobility prediction,Telecom cloud,Telecommunication system},
  month = {mar},
  number = {1},
  pages = {59--75},
  title = {{MPaaS: Mobility prediction as a service in telecom cloud}},
  url = {http://link.springer.com/10.1007/s10796-013-9476-z},
  volume = {16},
  year = {2014}
}
@inproceedings{Dilorenzo2014,
  abstract = {The deep penetration of mobile phones offers cities the ability to opportunistically monitor citizens' mobility and use datadriven insights to better plan and manage services. In this context, transit operators can leverage pervasive mobile sensing to better match observed demand for travel with their service offerings. In this paper we present AllAboard, an intelligent tool that analyses cellphone data to helps city authorities in exploring urban mobility and optimizing public transport. An interactive user interface allows transit operators to explore the travel demand in both space and time, evaluate the quality of service that a transit network provides to the citizens, and test scenarios for transit network improvements. The system has been tested using real telecommunication data for the city of Abidjan, Ivory Coast, and evaluated from a data mining, optimisation and user prospective. {\textcopyright} 2014 ACM.},
  address = {New York, New York, USA},
  author = {Di lorenzo, Giusy and Sbodio, Marco Luca and Calabrese, Francesco and Berlingerio, Michele and Nair, Rahul and Pinelli, Fabio},
  booktitle = {Proceedings of the 19th international conference on Intelligent User Interfaces - IUI '14},
  doi = {10.1145/2557500.2557532},
  isbn = {9781450321846},
  pages = {335--340},
  publisher = {ACM Press},
  title = {{AllAboard}},
  url = {http://dl.acm.org/citation.cfm?doid=2557500.2557532},
  year = {2014}
}
@article{Calabrese2014,
  abstract = {The recent development of telecommunication networks is producing an unprecedented wealth of information and, as a consequence, an increasing interest in analyzing such data both from telecoms and from other stakeholders' points of view. In particular, mobile phone datasets offer access to insights into urban dynamics and human activities at an unprecedented scale and level of detail, representing a huge opportunity for research and real-world applications. This article surveys the new ideas and techniques related to the use of telecommunication data for urban sensing. We outline the data that can be collected from telecommunication networks as well as their strengths and weaknesses with a particular focus on urban sensing. We survey existing filtering and processing techniques to extract insights from this data and summarize them to provide recommendations on which datasets and techniques to use for specific urban sensing applications. Finally, we discuss a number of challenges and open research areas currently being faced in this field. We strongly believe the material and recommendations presented here will become increasingly important as mobile phone network datasets are becoming more accessible to the research community.},
  author = {Calabrese, Francesco and Ferrari, Laura and Blondel, Vincent D.},
  doi = {10.1145/2655691},
  isbn = {1000142405274},
  issn = {03600300},
  journal = {ACM Computing Surveys},
  month = {nov},
  number = {2},
  pages = {1--20},
  title = {{Urban Sensing Using Mobile Phone Network Data: A Survey of Research}},
  url = {http://dl.acm.org/citation.cfm?doid=2658850.2655691},
  volume = {47},
  year = {2014}
}
@article{Zheng2014,
  abstract = {Urbanization's rapid progress has modernized many people's lives, but also engendered big issues, such as traffic congestion, energy consumption, and pollution. Urban computing aims to tackle these issues by using the data that has been generated in cities, e.g., traffic flow, human mobility and geographical data. Urban computing connects urban sensing, data management, data analytics, and service providing into a recurrent process for an unobtrusive and continuous improvement of people's lives, city operation systems, and the environment. Urban computing is an interdisciplinary field where computer sciences meet conventional city-related fields, like transportation, civil engineering, environment, economy, ecology, and sociology, in the context of urban spaces. This article first introduces the concept of urban computing, discussing its general framework and key challenges from the perspective of computer sciences. Secondly, we classify the applications of urban computing into seven categories, consisting of urban planning, transportation, the environment, energy, social, economy, and public safety {\&} security, presenting representative scenarios in each category. Thirdly, we summarize the typical technologies that are needed in urban computing into four folds, which are about urban sensing, urban data management, knowledge fusion across heterogeneous data, and urban data visualization. Finally, we outlook the future of urban computing, suggesting a few research topics that are somehow missing in the community},
  author = {Zheng, Yu and Capra, Licia and Wolfson, Ouri and Yang, Hai},
  doi = {10.1145/2629592},
  isbn = {2157-6904},
  issn = {21576904},
  journal = {ACM Transactions on Intelligent Systems and Technology},
  month = {sep},
  number = {3},
  pages = {1--55},
  title = {{Urban Computing}},
  url = {http://dl.acm.org/citation.cfm?doid=2648782.2629592},
  volume = {5},
  year = {2014}
}
@inproceedings{Xue2014,
  abstract = {Tourism industry has become a key economic driver for Singapore. Understanding the behaviors of tourists is very important for the government and private sectors, e.g., restaurants, hotels and advertising companies, to improve their existing services or create new business opportunities. In this joint work with Singapore's Land Transport Authority (LTA), we innovatively apply machine learning techniques to identity the tourists among public commuters using the public transportation data provided by LTA. On successful identification, the travelling patterns of tourists are then revealed and thus allow further analyses to be carried out such as on their favorite destinations, region of stay, etc. Technically, we model the tourists identification as a classification problem, and design an iterative learning algorithm to perform inference with limited prior knowledge and labeled data. We show the superiority of our algorithm with performance evaluation and comparison with other state-of-the-art learning algorithms. Further, we build an interactive web-based system for answering queries regarding the moving patterns of the tourists, which can be used by stakeholders to gain insight into tourists' travelling behaviors in Singapore. {\textcopyright} 2014 ACM.},
  address = {New York, New York, USA},
  author = {Xue, Mingqiang and Wu, Huayu and Chen, Wei and Goh, Gin Howe},
  booktitle = {Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '14},
  doi = {10.1145/2623330.2623352},
  isbn = {9781450329569},
  pages = {1779--1788},
  publisher = {ACM Press},
  title = {{Identifying tourists from public transport commuters}},
  url = {http://dl.acm.org/citation.cfm?doid=2623330.2623352},
  year = {2014}
}
@inproceedings{Cuttone2014,
  abstract = {Understanding both collective and personal human mobility is a central topic in Computational Social Science. Smartphone sensing data is emerging as a promising source for studying human mobility. However, most literature focuses on high-precision GPS positioning and high-frequency sampling, which is not always feasible in a longitudinal study or for everyday applications because location sensing has a high battery cost. In this paper we study the feasibility of inferring human mobility from sparse, low accuracy mobile sensing data. We validate our results using participants' location diaries, and analyze the inferred geographical networks, the time spent at different places, and the number of unique places over time. Our results suggest that low resolution data allows accurate inference of human mobility patterns.},
  address = {New York, New York, USA},
  author = {Cuttone, Andrea and Lehmann, Sune and Larsen, Jakob Eg},
  booktitle = {Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct Publication - UbiComp '14 Adjunct},
  doi = {10.1145/2638728.2641283},
  isbn = {9781450330473},
  pages = {995--1004},
  publisher = {ACM Press},
  title = {{Inferring human mobility from sparse low accuracy mobile sensing data}},
  url = {http://dl.acm.org/citation.cfm?doid=2638728.2641283},
  year = {2014}
}
@inproceedings{Felde2014,
  author = {Felde, Imre and Nadai, Laszlo and Mezei, Miklos and Bognar, Gabor},
  booktitle = {2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
  doi = {10.1109/SMC.2014.6974446},
  isbn = {978-1-4799-3840-7},
  issn = {1062922X},
  keywords = {cell phone,cellular network,urban mobility},
  month = {oct},
  pages = {3360--3363},
  publisher = {IEEE},
  title = {{Characterization of of urban traffic by using mobile phone traces}},
  url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6974446},
  year = {2014}
}
@article{Annafari2014,
  abstract = {Most studies in the mobile communication field focus on the acceptance of the technology rather than the resistance of it, a trend that makes researchers try to understand only the powerful actors in society. Instead, this paper explores the socio-economic characteristics of mobile phone service have-nots. Based on an analysis of samples from three consecutive nationwide annual surveys in Sweden, this study finds that two socio-economic factors – age and the household income – remain significant to explain non-usage of mobile phone services. Other variables dynamically change over time without a significant effect. This finding supports the argument that most socio-economic factors are transient at different stages of the adoption of innovation. Since the benefits of mobile phones are related to social networks (the more people you know, the more beneficial), it is not surprising that, in the long run, elderly people with low income, who typically have a decreasing social network, find this technology no longer purposeful and finally refuse it. This indicates that the status of the have-nots may not reflect socio-economic inequalities in general, but rather individuals' preference when managing their social situation. This is relevant with the argument that a universal service policy should be based on connectivity, that is, people's need for communication rather than solely promoting subsidizing a particular technology or service. The policy, therefore, should consider the technological frame sharing – the interpretation of the technology shared by members of a relevant social group, that is, users, service providers and regulators, to bring a more socially constructed technology that can protect individuals with less socio-economic power from being socially excluded.},
  author = {Annafari, Mohammad T. and Axelsson, Ann Sofie and Bohlin, Erik},
  doi = {10.1177/1461444813487954},
  isbn = {1461-4448},
  issn = {14617315},
  journal = {New Media and Society},
  keywords = {Connectivity,diffusion of innovation,have-nots,technological frame sharing,universal service policy,warm experts},
  month = {may},
  number = {3},
  pages = {415--433},
  title = {{A socio-economic exploration of mobile phone service have-nots in Sweden}},
  url = {http://journals.sagepub.com/doi/10.1177/1461444813487954},
  volume = {16},
  year = {2014}
}
@incollection{Schryen,
  author = {Schryen, Guido and Wex, Felix},
  booktitle = {International Journal of Information Systems for Crisis Response and Management},
  doi = {10.4018/ijiscram.2014010102},
  isbn = {2014010102},
  issn = {1937-9390},
  number = {1},
  pages = {38--64},
  publisher = {IGI Global},
  title = {{Risk Reduction in Natural Disaster Management Through Information Systems}},
  url = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiscram.2014010102},
  volume = {6},
  year = {2014}
}
@article{RODRIGUEZ2014,
  abstract = {Time plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion— when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on- going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.},
  author = {Rodriguez, Manuel Gomez and Leskovec, Jure and Balduzzi, David and Sch{\"{o}}lkopf, Bernhard},
  doi = {10.1017/nws.2014.3},
  isbn = {2050-1250},
  issn = {20501250},
  journal = {Network Science},
  keywords = {blogs,diffusion networks,information cascades,information networks,information propagation,meme tracking,news media,social networks},
  month = {apr},
  number = {1},
  pages = {26--65},
  title = {{Uncovering the structure and temporal dynamics of information propagation}},
  url = {http://www.journals.cambridge.org/abstract{\_}S2050124214000034},
  volume = {2},
  year = {2014}
}
@inproceedings{Pastor-Escuredo2014a,
  abstract = {Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.},
  archiveprefix = {arXiv},
  arxivid = {1411.6574},
  author = {Pastor-Escuredo, David and Morales-Guzm{\'{a}}n, Alfredo and Torres-Fern{\'{a}}ndez, Yolanda and Bauer, Jean Martin and Wadhwa, Amit and Castro-Correa, Carlos and Romanoff, Liudmyla and Lee, Jong Gun and Rutherford, Alex and Frias-Martinez, Vanessa and Oliver, Nuria and Frias-Martinez, Enrique and Luengo-Oroz, Miguel},
  booktitle = {Proceedings of the 4th IEEE Global Humanitarian Technology Conference, GHTC 2014},
  doi = {10.1109/GHTC.2014.6970293},
  eprint = {1411.6574},
  isbn = {9781479971930},
  keywords = {Big Data for Development,Emergency Service Allocation,Human Behavior Modeling,Mobile Data Analysis,Natural Disaster Response},
  month = {oct},
  pages = {279--286},
  publisher = {IEEE},
  title = {{Flooding through the lens of mobile phone activity}},
  url = {http://ieeexplore.ieee.org/document/6970293/},
  year = {2014}
}
@article{Amini2014,
  abstract = {This study leverages mobile phone data to analyze human mobility patterns in a developing nation, especially in comparison to those of a more industrialized nation. Developing regions, such as the Ivory Coast, are marked by a number of factors that may influence mobility, such as less infrastructural coverage and maturity, less economic resources and stability, and in some cases, more cultural and language-based diversity. By comparing mobile phone data collected from the Ivory Coast to similar data collected in Portugal, we are able to highlight both qualitative and quantitative differences in mobility patterns - such as differences in likelihood to travel, as well as in the time required to travel - that are relevant to consideration on policy, infrastructure, and economic development. Our study illustrates how cultural and linguistic diversity in developing regions (such as Ivory Coast) can present challenges to mobility models that perform well and were conceptualized in less culturally diverse regions. Finally, we address these challenges by proposing novel techniques to assess the strength of borders in a regional partitioning scheme and to quantify the impact of border strength on mobility model accuracy.},
  archiveprefix = {arXiv},
  arxivid = {1401.5743},
  author = {Amini, Alexander and Kung, Kevin and Kang, Chaogui and Sobolevsky, Stanislav and Ratti, Carlo},
  doi = {10.1140/epjds31},
  eprint = {1401.5743},
  isbn = {0028-0836},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {Cultural diversity,Predictive human mobility,Social networks},
  month = {dec},
  number = {1},
  pages = {1--20},
  pmid = {25246403},
  title = {{The impact of social segregation on human mobility in developing and industrialized regions}},
  url = {http://www.epjdatascience.com/content/3/1/6},
  volume = {3},
  year = {2014}
}
@techreport{InstitutoNacionaldeEstadistica2014,
  address = {Santiago},
  author = {{Instituto Nacional de Estad{\'{i}}stica}},
  institution = {Instituto Nacional de Estad{\'{i}}sticas},
  pages = {1--87},
  title = {{Auditor{\'{i}}a T{\'{e}}cnica a La Base De Datos del levantamiento Censal a{\~{n}}o 2012 (Technical Evaluation of the 2012 Census Database)}},
  url = {http://historico.ine.cl/canales/chile{\_}estadistico/censos{\_}poblacion{\_}vivienda/auditoria-levantamiento-censal.pdf},
  year = {2014}
}
@inproceedings{Arai2014,
  address = {New York, New York, USA},
  author = {Arai, Ayumi and Witayangkurn, Apichon and Kanasugi, Hiroshi and Horanont, Teerayut and Shao, Xiaowei and Shibasaki, Ryosuke},
  booktitle = {Proceedings of the 12th International Conference on Advances in Mobile Computing and Multimedia - MoMM '14},
  doi = {10.1145/2684103.2684107},
  file = {::},
  isbn = {9781450330084},
  keywords = {Call Detail Records,Calling Behavior,Demographic attributes},
  pages = {95--104},
  publisher = {ACM Press},
  title = {{Understanding User Attributes from Calling Behavior}},
  url = {http://dl.acm.org/citation.cfm?doid=2684103.2684107},
  year = {2014}
}
@inproceedings{Sarraute2014,
  abstract = {Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We were able to detect significant differences in phone usage among different subgroups of the population. Our second contribution is to provide a novel methodology to predict demographic features (namely age and gender) of unlabeled users by leveraging individual calling patterns, as well as the structure of the communication graph. We provide details of the methodology and show experimental results on a real world dataset that involves millions of users.},
  archiveprefix = {arXiv},
  arxivid = {1511.06656},
  author = {Sarraute, Carlos and Blanc, Pablo and Burroni, Javier},
  booktitle = {Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on},
  doi = {10.1109/ASONAM.2014.6921683},
  eprint = {1511.06656},
  file = {::},
  isbn = {VO -},
  keywords = {Algorithm design and analysis,Machine learning algorithms,Mexican mobile phone users,Mexico,Mobile handsets,Prediction algorithms,Social network services,Sociology,Statistics,communication graph,individual calling patterns,mobile computing,mobile phone usage patterns,real world dataset},
  month = {nov},
  pages = {836--843},
  title = {{A study of age and gender seen through mobile phone usage patterns in Mexico}},
  url = {http://ieeexplore.ieee.org/document/6921683/},
  year = {2014}
}
@inproceedings{Sarraute2014a,
  abstract = {Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We were able to detect significant differences in phone usage among different subgroups of the population. Our second contribution is to provide a novel methodology to predict demographic features (namely age and gender) of unlabeled users by leveraging individual calling patterns, as well as the structure of the communication graph. We provide details of the methodology and show experimental results on a real world dataset that involves millions of users.},
  archiveprefix = {arXiv},
  arxivid = {1511.06656},
  author = {Sarraute, Carlos and Blanc, Pablo and Burroni, Javier},
  booktitle = {Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on},
  doi = {10.1109/ASONAM.2014.6921683},
  eprint = {1511.06656},
  isbn = {VO -},
  keywords = {Algorithm design and analysis,Machine learning algorithms,Mexican mobile phone users,Mexico,Mobile handsets,Prediction algorithms,Social network services,Sociology,Statistics,communication graph,individual calling patterns,mobile computing,mobile phone usage patterns,real world dataset},
  month = {aug},
  pages = {836--843},
  publisher = {IEEE},
  title = {{A study of age and gender seen through mobile phone usage patterns in Mexico}},
  url = {http://ieeexplore.ieee.org/document/6921683/},
  year = {2014}
}
@article{Louail2015,
  abstract = {Pervasive infrastructures, such as cell phone networks, enable to capture large amounts of human behavioral data but also provide information about the structure of cities and their dynamical properties. In this article, we focus on these last aspects by studying phone data recorded during 55 days in 31 Spanish cities. We first define an urban dilatation index which measures how the average distance between individuals evolves during the day, allowing us to highlight different types of city structure. We then focus on hotspots, the most crowded places in the city. We propose a parameter free method to detect them and to test the robustness of our results. The number of these hotspots scales sublinearly with the population size, a result in agreement with previous theoretical arguments and measures on employment datasets. We study the lifetime of these hotspots and show in particular that the hierarchy of permanent ones, which constitute the 'heart' of the city, is very stable whatever the size of the city. The spatial structure of these hotspots is also of interest and allows us to distinguish different categories of cities, from monocentric and "segregated" where the spatial distribution is very dependent on land use, to polycentric where the spatial mixing between land uses is much more important. These results point towards the possibility of a new, quantitative classification of cities using high resolution spatio-temporal data.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1401.4540v1},
  author = {Louail, Thomas and Lenormand, Maxime and {Cantu Ros}, Oliva G. and Picornell, Miguel and Herranz, Ricardo and Frias-Martinez, Enrique and Ramasco, Jos{\'{e}} J. and Barthelemy, Marc},
  doi = {10.1038/srep05276},
  eprint = {arXiv:1401.4540v1},
  isbn = {2045-2322},
  issn = {20452322},
  journal = {Scientific Reports},
  month = {may},
  number = {1},
  pages = {5276},
  pmid = {24923248},
  title = {{From mobile phone data to the spatial structure of cities}},
  url = {http://www.nature.com/articles/srep05276},
  volume = {4},
  year = {2014}
}
@article{Liu2014,
  abstract = {Activity-based micro-simulation transportation models typically predict 24-h activity-travel sequences for each individual in a study area. These sequences serve as a key input for travel demand analysis and forecasting in the region. However, despite their importance, the lack of a reliable benchmark to evaluate the generated sequences has hampered further development and application of the models. With the wide deployment of mobile phone devices today, we explore the possibility of using the travel behavioral information derived from mobile phone data to build such a validation measure. Our investigation consists of three steps. First, the daily trajectory of locations, where a user performed activities, is constructed from the mobile phone records. To account for the discrepancy between the stops revealed by the call data and the real location traces that the user has made, the daily trajectories are then transformed into actual travel sequences. Finally, all the derived sequences are classified into typical activity-travel patterns which, in combination with their relative frequencies, define an activity-travel profile. The established profile characterizes the current activity-travel behavior in the study area, and can thus be used as a benchmark for the assessment of the activity-based transportation models. By comparing the activity-travel profiles derived from the call data with statistics that stem from traditional activity-travel surveys, the validation potential is demonstrated. In addition, a sensitivity analysis is carried out to assess how the results are affected by the different parameter settings defined in the profiling process. {\textcopyright} 2014 Elsevier Ltd. All rights reserved.},
  author = {Liu, Feng and Janssens, Davy and Cui, Jianxun and Wang, Yunpeng and Wets, Geert and Cools, Mario},
  doi = {10.1016/j.eswa.2014.03.054},
  isbn = {0957-4174},
  issn = {09574174},
  journal = {Expert Systems with Applications},
  keywords = {Activity-based transportation models,Activity-travel sequences,Mobile phone data,Travel surveys},
  month = {oct},
  number = {14},
  pages = {6174--6189},
  title = {{Building a validation measure for activity-based transportation models based on mobile phone data}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0957417414002036},
  volume = {41},
  year = {2014}
}
@article{Blumenstock2015,
  abstract = {Accurate and timely estimates of population characteristics are a critical input to social and economic research and policy. In industrialized economies, novel sources of data are enabling new approaches to demographic profiling, but in developing countries, fewer sources of big data exist. We show that an individuals past history of mobile phone use can be used to infer his or her socioeconomic status. Furthermore, we demonstrate that the predicted attributes of millions of individuals can, in turn, accurately reconstruct the distribution of wealth of an entire nation or to infer the asset distribution of microregions composed of just a few households. In resource-constrained environments where censuses and household surveys are rare, this approach creates an option for gathering localized and timely information at a fraction of the cost of traditional methods.},
  author = {Blumenstock, Joshua and Cadamuro, Gabriel and On, Robert},
  doi = {10.1126/science.aac4420},
  file = {::},
  isbn = {10.1126/science.aac4420},
  issn = {10959203},
  journal = {Science},
  month = {nov},
  number = {6264},
  pages = {1073--1076},
  pmid = {26612950},
  publisher = {American Association for the Advancement of Science},
  title = {{Predicting poverty and wealth from mobile phone metadata}},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/26612950},
  volume = {350},
  year = {2015}
}
@article{Bjorkegren2017,
  abstract = {Many households in developing countries lack formal financial histories, making it difficult for banks to extend loans, and for potential borrowers to receive them. However, many of these households have mobile phones, which generate rich data about behavior. This paper shows that behavioral signatures in mobile phone data predict loan default, using call records matched to loan outcomes. In a middle income South American country, individuals in the highest quintile of risk by our measure are 2.8 times more likely to default than those in the lowest quintile. On our sample of individuals with (thin) financial histories, our method outperforms models using credit bureau information, both within time and when tested on a different time period. The method forms the basis for new forms of lending that reach the unbanked. },
  archiveprefix = {arXiv},
  arxivid = {1712.05840},
  author = {Bjorkegren, Daniel and Grissen, Darrell},
  doi = {10.2139/ssrn.2611775},
  eprint = {1712.05840},
  file = {::},
  journal = {Ssrn},
  keywords = {O16,big data,credit scoring,microfinance,mobile phones},
  month = {dec},
  title = {{Behavior Revealed in Mobile Phone Usage Predicts Loan Repayment}},
  url = {http://arxiv.org/abs/1712.05840},
  year = {2015}
}
@article{Li2014,
  abstract = {Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.},
  archiveprefix = {arXiv},
  arxivid = {1402.6573},
  author = {Li, Ming-Xia and Jiang, Zhi-Qiang and Xie, Wen-Jie and Miccich{\`{e}}, Salvatore and Tumminello, Michele and Zhou, Wei-Xing and Mantegna, Rosario N.},
  doi = {10.1038/srep05132},
  eprint = {1402.6573},
  file = {::},
  isbn = {2045-2322 (Electronic)$\backslash$r2045-2322 (Linking)},
  issn = {2045-2322},
  journal = {Scientific Reports},
  month = {feb},
  number = {1},
  pages = {5132},
  title = {{A comparative analysis of the statistical properties of large mobile phone calling networks}},
  url = {http://www.nature.com/articles/srep05132},
  volume = {4},
  year = {2015}
}
@article{Williams2014,
  abstract = {In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never before possible with censuses, surveys or other existing data collection techniques. There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used. However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context. New measures would best be developed immediately as they will influence future studies of mobility using mobile phone data. In this article, we do exactly this. We discuss problems with existing mobile phone based measures of mobility and describe new methods for measuring mobility that address these concerns. Our measures of mobility, which incorporate both mobile phone records and detailed GIS data, are designed to address the spatial nature of human mobility, to remain independent of social characteristics of context, and to be comparable across geographic regions and time. We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.},
  archiveprefix = {arXiv},
  arxivid = {1408.5420},
  author = {Williams, Nathalie E. and Thomas, Timothy A. and Dunbar, Matthew and Eagle, Nathan and Dobra, Adrian},
  doi = {10.1371/journal.pone.0133630},
  eprint = {1408.5420},
  file = {::},
  isbn = {1932-6203},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {aug},
  number = {7},
  pmid = {26192322},
  title = {{Measures of human mobility using mobile phone records enhanced with GIS data}},
  url = {http://arxiv.org/abs/1408.5420 http://dx.doi.org/10.1371/journal.pone.0133630},
  volume = {10},
  year = {2015}
}
@article{Dobra2014,
  abstract = {With the aim to contribute to humanitarian response to disasters and violent events, scientists have proposed the development of analytical tools that could identify emergency events in real-time, using mobile phone data. The assumption is that dramatic and discrete changes in behavior, measured with mobile phone data, will indicate extreme events. In this study, we propose an efficient system for spatiotemporal detection of behavioral anomalies from mobile phone data and compare sites with behavioral anomalies to an extensive database of emergency and non-emergency events in Rwanda. Our methodology successfully captures anomalous behavioral patterns associated with a broad range of events, from religious and official holidays to earthquakes, floods, violence against civilians and protests. Our results suggest that human behavioral responses to extreme events are complex and multi-dimensional, including extreme increases and decreases in both calling and movement behaviors. We also find significant temporal and spatial variance in responses to extreme events. Our behavioral anomaly detection system and extensive discussion of results are a significant contribution to the long-term project of creating an effective real-time event detection system with mobile phone data and we discuss the implications of our findings for future research to this end.},
  archiveprefix = {arXiv},
  arxivid = {1411.6179},
  author = {Dobra, Adrian and Williams, Nathalie E. and Eagle, Nathan},
  doi = {10.1371/journal.pone.0120449},
  eprint = {1411.6179},
  file = {::},
  isbn = {1932-6203},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {nov},
  number = {3},
  pmid = {25806954},
  title = {{Spatiotemporal detection of unusual human population behavior using mobile phone data}},
  url = {http://arxiv.org/abs/1411.6179 http://dx.doi.org/10.1371/journal.pone.0120449},
  volume = {10},
  year = {2015}
}
@article{Pastor-Escuredo2015,
  abstract = {Fires, lights at night and mobile phone activity have been separately used as proxy indicators of human activity with high potential for measuring human development. In this preliminary report, we develop some tools and methodologies to identify and visualize relations among remote sensing datasets containing fires and night lights information with mobile phone activity in Cote D'Ivoire from December 2011 to April 2012.},
  archiveprefix = {arXiv},
  arxivid = {1501.0549},
  author = {Pastor-Escuredo, David and Savy, Thierry and Luengo-Oroz, Miguel a.},
  eprint = {1501.0549},
  file = {::},
  keywords = {lattice theory,orthomodular,quantum logic,quantum mechanics},
  month = {jan},
  pages = {1--14},
  title = {{Can Fires, Night Lights, and Mobile Phones reveal behavioral fingerprints useful for Development?}},
  url = {http://arxiv.org/abs/1501.0549},
  year = {2015}
}
@article{Blondel2015,
  abstract = {In this paper, we review some advances made recently in the study of mobile phone datasets. This area of research has emerged a decade ago, with the increasing availability of large-scale anonymized datasets, and has grown into a stand-alone topic. We will survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.},
  archiveprefix = {arXiv},
  arxivid = {1502.03406},
  author = {Blondel, Vincent D. and Decuyper, Adeline and Krings, Gautier},
  doi = {10.1140/epjds/s13688-015-0046-0},
  eprint = {1502.03406},
  file = {::},
  isbn = {1536-1233 VO - 15},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {big data analysis,data mining,geographical networks,mobile phone datasets,social networks,temporal networks},
  month = {feb},
  number = {1},
  pages = {1--55},
  title = {{A survey of results on mobile phone datasets analysis}},
  url = {http://arxiv.org/abs/1502.03406},
  volume = {4},
  year = {2015}
}
@article{Martinez-Cesena2015,
  abstract = {Detailed knowledge of the energy needs at relatively high spatial and temporal resolution is crucial for the electricity infrastructure planning of a region. However, such information is typically limited by the scarcity of data on human activities, in particular in developing countries where electrification of rural areas is sought. The analysis of society-wide mobile phone records has recently proven to offer unprecedented insights into the spatio-temporal distribution of people, but this information has never been used to support electrification planning strategies anywhere and for rural areas in developing countries in particular. The aim of this project is the assessment of the contribution of mobile phone data for the development of bottom-up energy demand models, in order to enhance energy planning studies and existing electrification practices. More specifically, this work introduces a framework that combines mobile phone data analysis, socioeconomic and geo-referenced data analysis, and state-of-the-art energy infrastructure engineering techniques to assess the techno-economic feasibility of different centralized and decentralized electrification options for rural areas in a developing country. Specific electrification options considered include extensions of the existing medium voltage (MV) grid, diesel engine-based community-level Microgrids, and individual household-level solar photovoltaic (PV) systems. The framework and relevant methodology are demonstrated throughout the paper using the case of Senegal and the mobile phone data made available for the 'D4D-Senegal' innovation challenge. The results are extremely encouraging and highlight the potential of mobile phone data to support more efficient and economically attractive electrification plans.},
  archiveprefix = {arXiv},
  arxivid = {1504.03899},
  author = {Mart{\'{i}}nez-Cesena, Eduardo Alejandro and Mancarella, Pierluigi and Ndiaye, Mamadou and Schl{\"{a}}pfer, Markus},
  eprint = {1504.03899},
  file = {::},
  keywords = {Electrification,Microgrids,Photovoltaics,cellular networks,data,human dynamics,mobile phone},
  month = {apr},
  number = {Mv},
  pages = {9},
  title = {{Using Mobile Phone Data for Electricity Infrastructure Planning}},
  url = {http://arxiv.org/ftp/arxiv/papers/1504/1504.03899.pdf},
  year = {2015}
}
@article{Dong2015,
  abstract = {The pervasiveness and availability of mobile phone data offer the opportunity of discovering usable knowledge about crowd behaviors in urban environments. Cities can leverage such knowledge in order to provide better services (e.g., public transport planning, optimized resource allocation) and safer cities. Call Detail Record (CDR) data represents a practical data source to detect and monitor unusual events considering the high level of mobile phone penetration, compared with GPS equipped and open devices. In this paper, we provide a methodology that is able to detect unusual events from CDR data that typically has low accuracy in terms of space and time resolution. Moreover, we introduce a concept of unusual event that involves a large amount of people who expose an unusual mobility behavior. Our careful consideration of the issues that come from coarse-grained CDR data ultimately leads to a completely general framework that can detect unusual crowd events from CDR data effectively and efficiently. Through extensive experiments on real-world CDR data for a large city in Africa, we demonstrate that our method can detect unusual events with 16{\%} higher recall and over 10 times higher precision, compared to state-of-the-art methods. We implement a visual analytics prototype system to help end users analyze detected unusual crowd events to best suit different application scenarios. To the best of our knowledge, this is the first work on the detection of unusual events from CDR data with considerations of its temporal and spatial sparseness and distinction between user unusual activities and daily routines.},
  archiveprefix = {arXiv},
  arxivid = {1504.03643},
  author = {Dong, Yuxiao and Pinelli, Fabio and Gkoufas, Yiannis and Nabi, Zubair and Calabrese, Francesco and Chawla, Nitesh V.},
  doi = {10.1007/978-3-319-23525-7_29},
  eprint = {1504.03643},
  file = {::},
  isbn = {9783319235240},
  issn = {16113349},
  journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  month = {apr},
  pages = {474--492},
  pmid = {22183238},
  title = {{Inferring unusual crowd events from mobile phone call detail records}},
  url = {http://arxiv.org/abs/1504.03643},
  volume = {9285},
  year = {2015}
}
@article{Toole2015,
  abstract = {Can data from mobile phones be used to observe economic shocks and their consequences at multiple scales? Here we present novel methods to detect mass layoffs, identify individuals affected by them and predict changes in aggregate unemployment rates using call detail records (CDRs) from mobile phones. Using the closure of a large manufacturing plant as a case study, we first describe a structural break model to correctly detect the date of a mass layoff and estimate its size. We then use a Bayesian classification model to identify affected individuals by observing changes in calling behaviour following the plant's closure. For these affected individuals, we observe significant declines in social behaviour and mobility following job loss. Using the features identified at the micro level, we show that the same changes in these calling behaviours, aggregated at the regional level, can improve forecasts of macro unemployment rates. These methods and results highlight promise of new data resources to measure microeconomic behaviour and improve estimates of critical economic indicators.},
  archive = {arXiv},
  arxivid = {1505.06791},
  author = {Toole, Jameson L. and Lin, Yu Ru and Muehlegger, Erich and Shoag, Daniel and Gonz{\'{a}}lez, Marta C. and Lazer, David},
  doi = {10.1098/rsif.2015.0185},
  eprint = {1505.06791},
  file = {::},
  isbn = {1742-5689},
  issn = {17425662},
  journal = {Journal of the Royal Society Interface},
  keywords = {Complex systems,Computational social science,Mobility,Social networks,Unemployment},
  month = {may},
  number = {107},
  pmid = {26018965},
  title = {{Tracking employment shocks using mobile phone data}},
  url = {http://arxiv.org/abs/1505.06791},
  volume = {12},
  year = {2015}
}
@article{Aledavood2015,
  abstract = {Humans follow circadian rhythms, visible in their activity levels as well as physiological and psychological factors. Such rhythms are also visible in electronic communication records, where the aggregated activity levels of e.g. mobile telephone calls or Wikipedia edits are known to follow their own daily patterns. Here, we study the daily communication patterns of 24 individuals over 18 months, and show that each individual has a different, persistent communication pattern. These patterns may differ for calls and text messages, which points towards calls and texts serving a different role in communication. For both calls and texts, evenings play a special role. There are also differences in the daily patterns of males and females both for calls and texts, both in how they communicate with individuals of the same gender vs. opposite gender, and also in how communication is allocated at social ties of different nature (kin ties vs. non-kin ties). Taken together, our results show that there is an unexpected richness to the daily communication patterns, from different types of ties being activated at different times of day to different roles of communication channels and gender differences.},
  archiveprefix = {arXiv},
  arxivid = {1507.04596},
  author = {Aledavood, Talayeh and L{\'{o}}pez, Eduardo and Roberts, Sam G. B. and Reed-Tsochas, Felix and Moro, Esteban and Dunbar, Robin I. M. and Saram{\"{a}}ki, Jari},
  doi = {10.1007/978-3-319-29228-1_18},
  eprint = {1507.04596},
  month = {jul},
  title = {{Channel-Specific Daily Patterns in Mobile Phone Communication}},
  url = {http://arxiv.org/abs/1507.04596},
  year = {2015}
}
@article{Li2015,
  abstract = {People in modern societies form different social networks through numerous means of communication. These communication networks reflect different aspects of human's societal structure. The billing records of calls among mobile phone users enable us to construct a directed calling network (DCN) and its Bonferroni network (SVDCN) in which the preferential communications are statistically validated. Here we perform a comparative investigation of the cliques of the original DCN and its SVDCN constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that the statistical properties of the cliques of the two calling networks are qualitatively similar and the clique members in the DCN and the SVDCN exhibit idiosyncratic behaviors quantitatively. Members in large cliques are found to be spatially close to each other. Based on the clique degree profile of each mobile phone user, the most active users in the two calling networks can be classified in to several groups. The users in different groups are found to have different calling behaviors. Our study unveils interesting communication behaviors among mobile phone users that are densely connected to each other.},
  archiveprefix = {arXiv},
  arxivid = {1509.06197},
  author = {Li, Ming Xia and Xie, Wen Jie and Jiang, Zhi Qiang and Zhou, Wei Xing},
  doi = {10.1088/1742-5468/2015/11/P11007},
  eprint = {1509.06197},
  file = {::},
  issn = {17425468},
  journal = {Journal of Statistical Mechanics: Theory and Experiment},
  keywords = {communication,networks,random graphs,socio-economic networks,supply and information networks},
  month = {sep},
  number = {11},
  title = {{Communication cliques in mobile phone calling networks}},
  url = {http://arxiv.org/abs/1509.06197 http://dx.doi.org/10.1088/1742-5468/2015/11/P11007},
  volume = {2015},
  year = {2015}
}
@article{Brea2015,
  abstract = {We study the structure of the social graph of mobile phone users in the country of Mexico, with a focus on demographic attributes of the users (more specifically the users' age). We examine assortativity patterns in the graph, and observe a strong age homophily in the communications preferences. We propose a graph based algorithm for the prediction of the age of mobile phone users. The algorithm exploits the topology of the mobile phone network, together with a subset of known users ages (seeds), to infer the age of remaining users. We provide the details of the methodology, and show experimental results on a network GT with more than 70 million users. By carefully examining the topological relations of the seeds to the rest of the nodes in GT, we find topological metrics which have a direct influence on the performance of the algorithm. In particular we characterize subsets of users for which the accuracy of the algorithm is 62{\%} when predicting between 4 age categories (whereas a pure random guess would yield an accuracy of 25{\%}). We also show that we can use the probabilistic information computed by the algorithm to further increase its inference power to 72{\%} on a significant subset of users.},
  archiveprefix = {arXiv},
  arxivid = {1511.07337},
  author = {Brea, Jorge and Burroni, Javier and Minnoni, Martin and Sarraute, Carlos},
  doi = {10.1145/2659480.2659492},
  eprint = {1511.07337},
  file = {::},
  isbn = {9781450331920},
  month = {nov},
  title = {{Harnessing Mobile Phone Social Network Topology to Infer Users Demographic Attributes}},
  url = {http://arxiv.org/abs/1511.07337{\%}0Ahttp://dx.doi.org/10.1145/2659480.2659492},
  year = {2015}
}
@article{Nasim2015,
  abstract = {In this paper we predict outgoing mobile phone calls using a machine learning approach. We analyze to which extent the activity of mobile phone users is predictable. The premise is that mobile phone users exhibit temporal regularity in their interactions with majority of their contacts. In the sociological context, most social interactions have fairly reliable temporal regularity. If we quantify the extension of this behavior to interactions on mobile phones we expect that caller-callee interaction is not merely a result of randomness, rather it exhibits a temporal pattern. To this end, we tested our approach on an anonymized mobile phone usage dataset collected specifically for analyzing temporal patterns in mobile phone communication. The data consists of 783 users and more than 12,000 caller-callee pairs. The results show that users' historic calling patterns can predict future calls with reasonable accuracy.},
  archiveprefix = {arXiv},
  arxivid = {1512.08061},
  author = {Nasim, M and Rextin, A and Khan, N and Malik, MM},
  eprint = {1512.08061},
  file = {::},
  journal = {arXiv preprint arXiv:1512.08061},
  month = {dec},
  title = {{On Temporal Regularity in Social Interactions: Predicting Mobile Phone Calls}},
  url = {http://arxiv.org/abs/1512.08061},
  year = {2015}
}
@article{Janecek2015,
  abstract = {Mobile cellular networks can serve as ubiquitous sensors for physical mobility. We propose a method to infer vehicle travel times on highways and to detect road congestion in real-time, based solely on anonymized signaling data collected from a mobile cellular network. Most previous studies have considered data generated from mobile devices active in calls, namely Call Detail Records (CDR), an approach that limits the number of observable devices to a small fraction of the whole population. Our approach overcomes this drawback by exploiting the whole set of signaling events generated by both idle and active devices. While idle devices contribute with a large volume of spatially coarse-grained mobility data, active devices provide finer-grained spatial accuracy for a limited subset of devices. The combined use of data from idle and active devices improves congestion detection performance in terms of coverage, accuracy, and timeliness. We apply our method to real mobile signaling data obtained from an operational network during a one-month period on a sample highway segment in the proximity of a European city, and present an extensive validation study based on ground-truth obtained from a rich set of reference datasources - road sensor data, toll data, taxi floating car data, and radio broadcast messages.},
  author = {Janecek, Andreas and Valerio, Danilo and Hummel, Karin Anna and Ricciato, Fabio and Hlavacs, Helmut},
  doi = {10.1109/TITS.2015.2413215},
  issn = {15249050},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  keywords = {Cellular floating car data,large mobility data sets,mobility sensor,road congestion detection,travel time estimation},
  month = {oct},
  number = {5},
  pages = {2551--2572},
  title = {{The Cellular Network as a Sensor: From Mobile Phone Data to Real-Time Road Traffic Monitoring}},
  url = {http://ieeexplore.ieee.org/document/7079458/},
  volume = {16},
  year = {2015}
}
@inproceedings{Khan2015,
  abstract = {{\textcopyright} 2015 IEEE.With the increasing use of mobile devices, now it is possible to collect different data about the day-to-day activities of personal life of the user. Call Detail Record (CDR) is the available dataset at large-scale, as they are already constantly collected by the mobile operator mostly for billing purpose. By examining this data it is possible to analyze the activities of the people in urban areas and discover the human behavioral patterns of their daily life. These datasets can be used for many applications that vary from urban and transportation planning to predictive analytics of human behavior. In our research work, we have proposed a hierarchical analytical model where this CDR Dataset is used to find facts on the daily life activities of urban users in multiple layers. In our model, only the raw CDR data are used as the input in the initial layer and the outputs from each consecutive layer is used as new input combined with the original CDR data in the next layers to find more detailed facts, e.g., traffic density in different areas in working days and holidays. So, the output in each layer is dependent on the results of the previous layers. This model utilized the CDR Dataset of one month collected from the Dhaka city, which is one of the most densely populated cities of the world. So, our main focus of this research work is to explore the usability of these types of dataset for innovative applications, such as urban planning, traffic monitoring and prediction, in a fashion more appropriate for densely populated areas of developing countries.},
  author = {Khan, F.H. and Ali, M.E. and Dev, H.},
  booktitle = {Proceedings of 2015 International Conference on Networking Systems and Security, NSysS 2015},
  doi = {10.1109/NSysS.2015.7043535},
  isbn = {9781479981267},
  month = {jan},
  number = {February},
  pages = {1--6},
  publisher = {IEEE},
  title = {{A hierarchical approach for identifying user activity patterns from mobile phone call detail records}},
  url = {http://ieeexplore.ieee.org/document/7043535/},
  year = {2015}
}
@book{InstituteofElectricalandElectronicsEngineers,
  abstract = {"Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers."},
  author = {{Institute of Electrical and Electronics Engineers}},
  booktitle = {IEEE Transactions on Big Data},
  doi = {10.1109/TBDATA.2015.2448892},
  issn = {2332-7790},
  number = {1},
  pages = {48--48},
  title = {{IEEE Transactions on Big Data}},
  url = {http://ieeexplore.ieee.org/document/7153000/},
  volume = {1},
  year = {2015}
}
@article{Wang2015b,
  abstract = {Trip chaining, especially during peak-hour commute trips, is an important aspect of travel behavior that impacts the private and social costs and benefits of urban passenger travel. Combining large-sample data from the 2009 National Household Travel Survey (NHTS) and the 2010 US Census, this study analyzes the relationship between the complexity of commute tours and the characteristics of not just commuters and their households, but also their neighborhoods and regions. Different from most existing studies, this analysis controls more detailed individual, household, employment, and location characteristics and important interactions. In particular, by linking the restricted-use location data of households and work places from the NHTS survey to the US Census data, this study quantifies the effects of job-end population and employment densities. Results confirm the important impact of socio-demographics (gender, household responsibilities, and flexible work schedule), which underwent significant changes in the recent past, but fail to identify strong effects of socio-economic status, the regional and local built environment, or gasoline price.},
  author = {Wang, Rui},
  doi = {10.1016/j.jtrangeo.2014.11.005},
  issn = {09666923},
  journal = {Journal of Transport Geography},
  keywords = {Commute,Stop,Tour,Trip chaining,US},
  month = {jul},
  pages = {109--118},
  title = {{The stops made by commuters: Evidence from the 2009 US National Household Travel Survey}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0966692314002415},
  volume = {47},
  year = {2015}
}
@article{Toole2015a,
  abstract = {Rapid urbanization is placing increasing stress on already burdened transportation infrastructure. Ubiquitous mobile computing and the massive data it generates presents new opportunities to measure the demand for this infrastructure, diagnose problems, and plan for the future. However, before these benefits can be realized, methods and models must be updated to integrate these new data sources into existing urban and transportation planning frameworks for estimating travel demand and infrastructure usage. While recent work has made great progress extracting valid and useful measurements from new data resources, few present end-to-end solutions that transform and integrate raw, massive data into estimates of travel demand and infrastructure performance. Here we present a flexible, modular, and computationally efficient software system to fill this gap. Our system estimates multiple aspects of travel demand using call detail records (CDRs) from mobile phones in conjunction with open- and crowdsourced geospatial data, census records, and surveys. We bring together numerous existing and new algorithms to generate representative origin-destination matrices, route trips through road networks constructed using open and crowd-sourced data repositories, and perform analytics on the system's output. We also present an online, interactive visualization platform to communicate these results to researchers, policy makers, and the public. We demonstrate the flexibility of this system by performing analyses on multiple cities around the globe. We hope this work will serve as unified and comprehensive guide to integrating new big data resources into customary transportation demand modeling.},
  archiveprefix = {arXiv},
  arxivid = {1403.0636},
  author = {Toole, Jameson L. and Colak, Serdar and Sturt, Bradley and Alexander, Lauren P. and Evsukoff, Alexandre and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1016/j.trc.2015.04.022},
  eprint = {1403.0636},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {Congestion,Location based services,Mobile phone data,Mobility,Road networks},
  month = {sep},
  pages = {162--177},
  title = {{The path most traveled: Travel demand estimation using big data resources}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X15001631},
  volume = {58},
  year = {2015}
}
@article{Widhalm2015,
  abstract = {Massive and passive data such as cell phone traces provide samples of the whereabouts and movements of individuals. These are a potential source of information for models of daily activities in a city. The main challenge is that phone traces have low spatial precision and are sparsely sampled in time, which requires a precise set of techniques for mining hidden valuable information they contain. Here we propose a method to reveal activity patterns that emerge from cell phone data by analyzing relational signatures of activity time, duration, and land use. First, we present a method of how to detect stays and extract a robust set of geolocated time stamps that represent trip chains. Second, we show how to cluster activities by combining the detected trip chains with land use data. This is accomplished by modeling the dependencies between activity type, trip scheduling, and land use types via a Relational Markov Network. We apply the method to two different kinds of mobile phone datasets from the metropolitan areas of Vienna, Austria and Boston, USA. The former data includes information from mobility management signals, while the latter are usual Call Detail Records. The resulting trip sequence patterns and activity scheduling from both datasets agree well with their respective city surveys, and we show that the inferred activity clusters are stable across different days and both cities. This method to infer activity patterns from cell phone data allows us to use these as a novel and cheaper data source for activity-based modeling and travel behavior studies.},
  author = {Widhalm, Peter and Yang, Yingxiang and Ulm, Michael and Athavale, Shounak and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1007/s11116-015-9598-x},
  isbn = {0049-4488},
  issn = {15729435},
  journal = {Transportation},
  keywords = {Activity recognition,Activity-based models,Cell phone data,Mobility patterns,Relational Markov network,Unsupervised learning},
  month = {jul},
  number = {4},
  pages = {597--623},
  title = {{Discovering urban activity patterns in cell phone data}},
  url = {http://link.springer.com/10.1007/s11116-015-9598-x},
  volume = {42},
  year = {2015}
}
@article{Alexander2015,
  abstract = {In this work, we present methods to estimate average daily origin-destination trips from triangulated mobile phone records of millions of anonymized users. These records are first converted into clustered locations at which users engage in activities for an observed duration. These locations are inferred to be home, work, or other depending on observation frequency, day of week, and time of day, and represent a user's origins and destinations. Since the arrival time and duration at these locations reflect the observed (based on phone usage) rather than true arrival time and duration of a user, we probabilistically infer departure time using survey data on trips in major US cities. Trips are then constructed for each user between two consecutive observations in a day. These trips are multiplied by expansion factors based on the population of a user's home Census Tract and divided by the number of days on which we observed the user, distilling average daily trips. Aggregating individuals' daily trips by Census Tract pair, hour of the day, and trip purpose results in trip matrices that form the basis for much of the analysis and modeling that inform transportation planning and investments. The applicability of the proposed methodology is supported by validation against the temporal and spatial distributions of trips reported in local and national surveys.},
  author = {Alexander, Lauren and Jiang, Shan and Murga, Mikel and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1016/j.trc.2015.02.018},
  isbn = {0968-090X},
  issn = {0968090X},
  journal = {Transp. Res. Part C: Emerging Tech.},
  keywords = {Data mining,Human mobility,Mobile phone data,Travel surveys,Trip distribution,Trip production and attraction},
  month = {sep},
  pages = {240--250},
  title = {{Origin-destination trips by purpose and time of day inferred from mobile phone data}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X1500073X},
  volume = {58},
  year = {2015}
}
@article{Zheng2015,
  abstract = {The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Many techniques have been proposed for processing, managing, and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into trajectory data mining, providing a panorama of the field as well as the scope of its research topics. Following a road map from the derivation of trajectory data, to trajectory data preprocessing, to trajectory data management, and to a variety of mining tasks (such as trajectory pattern mining, outlier detection, and trajectory classification), the survey explores the connections, correlations, and differences among these existing techniques. This survey also introduces the methods that transform trajectories into other data formats, such as graphs, matrices, and tensors, to which more data mining and machine learning techniques can be applied. Finally, some public trajectory datasets are presented. This survey can help shape the field of trajectory data mining, providing a quick understanding of this field to the community.},
  author = {Zheng, Yu},
  doi = {10.1145/2743025},
  isbn = {2157-6904},
  issn = {21576904},
  journal = {ACM Transactions on Intelligent Systems and Technology},
  month = {may},
  number = {3},
  pages = {1--41},
  title = {{Trajectory Data Mining}},
  url = {http://dl.acm.org/citation.cfm?doid=2764959.2743025},
  volume = {6},
  year = {2015}
}
@article{Phithakkitnukoon2015,
  abstract = {This article describes a framework that capitalizes on the large-scale opportunistic mobile sensing approach for tourist behavior analysis. The article describes the use of massive mobile phone GPS location records to study tourist travel behavior, in particular, number of trips made, time spent at destinations, and mode of transportation used. Moreover, this study examined the relationship between personal mobility and tourist travel behavior and offered a number of interesting insights that are useful for tourism, such as tourist flows, top tourist destinations or origins, top destination types, top modes of transportation in terms of time spent and distance traveled, and how personal mobility information can be used to estimate the likelihood in tourist travel behavior, i.e., number of trips, time spent at destinations, and trip distance. Furthermore, the article describes an application developed based on the analysis in this study that allows the user to observe touristic, non-touristic, and commuting trips along with home and workplace locations as well as tourist flows, which can be useful for urban planners, transportation management, and tourism authorities.},
  author = {Phithakkitnukoon, Santi and Horanont, Teerayut and Witayangkurn, Apichon and Siri, Raktida and Sekimoto, Yoshihide and Shibasaki, Ryosuke},
  doi = {10.1016/j.pmcj.2014.07.003},
  isbn = {1574-1192},
  issn = {15741192},
  journal = {Pervasive and Mobile Computing},
  keywords = {GPS location traces,Mobile sensing,Mobility pattern,Tourist behavior},
  month = {apr},
  pages = {18--39},
  title = {{Understanding tourist behavior using large-scale mobile sensing approach: A case study of mobile phone users in Japan}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1574119214001321},
  volume = {18},
  year = {2015}
}
@inproceedings{Vanderhulst2015,
  abstract = {We present the design, implementation and evaluation of a novel human encounter detection framework for measuring and analysing human behaviour in social settings. We pro-pose the use of WiFi probes, management frames of WiFi, that periodically radiate from mobile devices (as proxies for humans), and existing WiFi access points to automatically capture radio signals and detect human copresence. Based on the spatio-temporal properties of this copresence and their interplay we defined a model, borrowing theories from so-ciology, to detect human encounters – short-lived, sponta-neous human interactions. We evaluated our framework us-ing controlled and in-the-wild experiments yielding a detec-tion performance of 96{\%} and 86{\%} respectively. As such, our framework opens up interesting opportunities for designing proxemic and group applications, as well as conducting large-scale studies in the areas of computational social sciences.},
  address = {New York, New York, USA},
  author = {Vanderhulst, Geert and Mashhadi, Afra and Dashti, Marzieh and Kawsar, Fahim},
  booktitle = {Proceedings of the 14th International Conference on Mobile and Ubiquitous Multimedia - MUM '15},
  doi = {10.1145/2836041.2836050},
  isbn = {9781450336055},
  pages = {97--108},
  publisher = {ACM Press},
  title = {{Detecting human encounters from WiFi radio signals}},
  url = {https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b{\&}scp=84959262422{\&}origin=inward{\%}5Cnpapers3://publication/doi/10.1145/2836041.2836050},
  volume = {30-Novembe},
  year = {2015}
}
@inproceedings{Wang2015a,
  abstract = {Many cognitive, behavioral, and environmental factors im- pact student learning during college. The SmartGPA study uses passive sensing data and self-reports from students' smartphones to understand individual behavioral differences between high and low performers during a single 10-week term. We propose new methods for better understanding study (e.g., study duration) and social (e.g., partying) behav- ior of a group of undergraduates. We show that there are a number of important behavioral factors automatically in- ferred from smartphones that significantly correlate with term and cumulative GPA, including time series analysis of ac- tivity, conversational interaction, mobility, class attendance, studying, and partying. We propose a simple model based on linear regression with lasso regularization that can accu- rately predict cumulative GPA. The predicted GPA strongly correlates with the ground truth from students' transcripts (r = 0.81 and p {\textless} 0.001) and predicts GPA within ±0.179 of the reported grades. Our results open the way for novel interventions to improve academic performance.},
  address = {New York, New York, USA},
  author = {Wang, Rui and Harari, Gabriella and Hao, Peilin and Zhou, Xia and Campbell, Andrew T.},
  booktitle = {Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15},
  doi = {10.1145/2750858.2804251},
  isbn = {9781450335744},
  pages = {295--306},
  publisher = {ACM Press},
  title = {{SmartGPA}},
  url = {http://dl.acm.org/citation.cfm?doid=2750858.2804251},
  year = {2015}
}
@inproceedings{Furno2015,
  address = {New York, New York, USA},
  author = {Furno, Angelo and Stanica, Razvan and Fiore, Marco},
  booktitle = {Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15},
  doi = {10.1145/2808797.2810057},
  isbn = {9781450338547},
  pages = {689--696},
  publisher = {ACM Press},
  title = {{A Comparative Evaluation of Urban Fabric Detection Techniques Based on Mobile Traffic Data}},
  url = {http://dl.acm.org/citation.cfm?doid=2808797.2810057},
  year = {2015}
}
@article{Bogomolov2015,
  abstract = {The wealth of information provided by real-time streams of data has paved the way for life-changing technological advancements, improving the quality of life of people in many ways, from facilitating knowledge exchange to self-understanding and self-monitoring. Moreover, the analysis of anonymized and aggregated large-scale human behavioral data offers new possibilities to understand global patterns of human behavior and helps decision makers tackle problems of societal importance. In this article, we highlight the potential societal benefits derived from big data applications with a focus on citizen safety and crime prevention. First, we introduce the emergent new research area of big data for social good. Next, we detail a case study tackling the problem of crime hotspot classification, that is, the classification of which areas in a city are more likely to witness crimes based on past data. In the proposed approach we use demographic information along with human mobility characteristics as derived from anonymized and aggregated mobile network data. The hypothesis that aggregated human behavioral data captured from the mobile network infrastructure, in combination with basic demographic information, can be used to predict crime is supported by our findings. Our models, built on and evaluated against real crime data from London, obtain accuracy of almost 70{\%} when classifying whether a specific area in the city will be a crime hotspot or not in the following month.},
  author = {Bogomolov, Andrey and Lepri, Bruno and Staiano, Jacopo and Letouz{\'{e}}, Emmanuel and Oliver, Nuria and Pianesi, Fabio and Pentland, Alex},
  doi = {10.1089/big.2014.0054},
  isbn = {2167-6461},
  issn = {2167-6461},
  journal = {Big Data},
  month = {sep},
  number = {3},
  pages = {148--158},
  pmid = {27442957},
  title = {{Moves on the Street: Classifying Crime Hotspots Using Aggregated Anonymized Data on People Dynamics}},
  url = {http://online.liebertpub.com/doi/10.1089/big.2014.0054},
  volume = {3},
  year = {2015}
}
@article{Morales2015,
  abstract = {Towards the consolidation of peace and national development, Ivory Coast
must overcome the lack of cohesion, responsible for the emergence of two
civil wars in the last years. As in many African countries, ethnic
violence is a result of the way territories are organized and the
prevalence of some groups over others. Nowadays the increasing
availability of electronic data allows to quantify and unveil societal
relationships in an unprecedented way. In this sense, the present work
analyzes mobile phone data in order to provide information about the
regional and ethnic interactions in Ivory Coast. We accomplish so by
means of the construction and analysis of complex social networks with
several types of interactions, such as calling activity and human
mobility. We found that in a subregional scale, the ethnic identity
plays an important role in the communication patterns, while at the
interregional scale, other factors arise like economical interests and
available infrastructure.},
  author = {Morales, Alfredo Jose and Creixell, Werner and Borondo, Javier and Losada, Juan Carlos and Benito, Rosa Maria},
  doi = {10.3934/nhm.2015.10.87},
  issn = {1556-1801},
  journal = {Networks and Heterogeneous Media},
  month = {feb},
  number = {1},
  pages = {87--99},
  title = {{Characterizing ethnic interactions from human communication patterns in Ivory Coast}},
  url = {http://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=10841},
  volume = {10},
  year = {2015}
}
@inproceedings{Heimerl2015,
  abstract = {The smartphone has been touted as the technology of the 21st century. Global smartphone adoption rates are growing rapidly, up to over 24{\%} in 2014, with usage increasing 25{\%} in the last year. However, rural areas are often the last places to benefit from these technological trends. Utilizing cellular network registration logs, we explore the adoption and usage of smartphones in an extremely remote community in Indonesia. We found that 16{\%} of the phones in the area were smartphones (compared to between 1424{\%} in Indonesia). This shows that smartphone adoption in rural Indonesia is similar to the rest of the country. We also explored usage in the network, and found that smartphone users were more likely to text, especially to other smartphone users.},
  address = {New York, New York, USA},
  author = {Heimerl, Kurtis and Menon, Anuvind and Hasan, Shaddi and Ali, Kashif and Brewer, Eric and Parikh, Tapan},
  booktitle = {Proceedings of the Seventh International Conference on Information and Communication Technologies and Development - ICTD '15},
  doi = {10.1145/2737856.2737880},
  isbn = {9781450331630},
  pages = {1--4},
  publisher = {ACM Press},
  title = {{Analysis of smartphone adoption and usage in a rural community cellular network}},
  url = {http://dl.acm.org/citation.cfm?doid=2737856.2737880},
  year = {2015}
}
@article{Steenbruggen2015,
  abstract = {Abstract The use of mobile phone data provides new spatio-temporal tools for improving urban planning, and for reducing inefficiencies in present-day urban systems. Data from mobile phones, originally intended as a communication tool, are increasingly used as innovative tools in geography and social sciences research. Empirical studies on complex city systems from human-centred and urban dynamics perspectives provide new insights to develop promising applications for supporting smart city initiatives. This paper provides a comprehensive review and a typology of spatial studies on mobile phone data, and highlights the applicability of such digital data to develop innovative applications for enhanced urban management.},
  author = {Steenbruggen, John and Tranos, Emmanouil and Nijkamp, Peter},
  doi = {10.1016/j.telpol.2014.04.001},
  isbn = {03085961},
  issn = {03085961},
  journal = {Telecommunications Policy},
  keywords = {Mobile phone data,Smart cities,Urban management},
  month = {may},
  number = {3-4},
  pages = {335--346},
  title = {{Data from mobile phone operators: A tool for smarter cities?}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0308596114000603},
  volume = {39},
  year = {2015}
}
@incollection{Wu2015,
  author = {Wu, Tao and Fan, Yujie and Hong, Zhiling and Chen, Lifei},
  doi = {10.1007/978-3-319-25159-2_64},
  pages = {703--711},
  title = {{Subspace Clustering on Mobile Data for Discovering Circle of Friends}},
  url = {http://link.springer.com/10.1007/978-3-319-25159-2{\_}64},
  year = {2015}
}
@article{Taylor2015,
  abstract = {The use of digital communication technologies, and of mobile phones in particular, has seen an exponential rise in low- and middle-income countries over the last decade. These data, emitted as a byproduct of technologies such as mobile phone location information and calling metadata, have the potential to fill some of the problematic gaps in data resources available to country policymakers and international development organisations. Using three examples of current big data initiatives in the international development field, we examine the implications of these new types of data for development policy and planning: their advantages and drawbacks, emerging practices relating to their use, and how they potentially influence ideas and policies of development. We also assess the politics of these new types of digital data, which are often collected and processed by corporations or by researchers in industrialised countries. Our analysis indicates that these new data sources already represent an important complement to country-level statistics, but that there are currently important challenges which will need to addressed if the promises of big data in development are to be fulfilled.},
  author = {Taylor, Linnet and Schroeder, Ralph},
  doi = {10.1007/s10708-014-9603-5},
  isbn = {1070801496035},
  issn = {03432521},
  journal = {GeoJournal},
  keywords = {Big data,Development,Policy},
  month = {aug},
  number = {4},
  pages = {503--518},
  title = {{Is bigger better? The emergence of big data as a tool for international development policy}},
  url = {http://link.springer.com/10.1007/s10708-014-9603-5},
  volume = {80},
  year = {2015}
}
@article{Pappalardo2015,
  abstract = {The availability of massive digital traces of human whereabouts has offered a series of novel insights on the quantitative patterns characterizing human mobility. In particular, numerous recent studies have lead to an unexpected consensus: the considerable variability in the characteristic travelled distance of individuals coexists with a high degree of predictability of their future locations. Here we shed light on this surprising coexistence by systematically investigating the impact of recurrent mobility on the characteristic distance travelled by individuals. Using both mobile phone and GPS data, we discover the existence of two distinct classes of individuals: returners and explorers. As existing models of human mobility cannot explain the existence of these two classes, we develop more realistic models able to capture the empirical findings. Finally, we show that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility patterns and social interactions.},
  author = {Pappalardo, Luca and Simini, Filippo and Rinzivillo, Salvatore and Pedreschi, Dino and Giannotti, Fosca and Barab{\'{a}}si, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1038/ncomms9166},
  isbn = {2041-1723},
  issn = {20411723},
  journal = {Nature Communications},
  month = {dec},
  number = {1},
  pages = {8166},
  pmid = {26349016},
  title = {{Returners and explorers dichotomy in human mobility}},
  url = {http://www.nature.com/articles/ncomms9166},
  volume = {6},
  year = {2015}
}
@inproceedings{Pappalardo2015a,
  abstract = {Big Data offer nowadays the potential capability of creating a digital nervous system of our society, enabling the measurement, monitoring and prediction of relevant aspects of socio-economic phenomena in quasi real time. This potential has fueled, in the last few years, a growing interest around the usage of Big Data to support official statistics in the measurement of individual and collective economic well-being. In this work we study the relations between human mobility patterns and socioeconomic development. Starting from nation-wide mobile phone data we extract a measure of mobility volume and a measure of mobility diversity for each individual. We then aggregate the mobility measures at municipality level and investigate the correlations with external socio-economic indicators independently surveyed by an official statistics institute. We find three main results. First, aggregated human mobility patterns are correlated with these socio-economic indicators. Second, the diversity of mobility, defined in terms of entropy of the individual users' trajectories, exhibits the strongest correlation with the external socio-economic indicators. Third, the volume of mobility and the diversity of mobility show opposite correlations with the socioeconomic indicators. Our results, validated against a null model, open an interesting perspective to study human behavior through Big Data by means of new statistical indicators that quantify and possibly "nowcast" the socio-economic development of our society.},
  author = {Pappalardo, Luca and Pedreschi, Dino and Smoreda, Zbigniew and Giannotti, Fosca},
  booktitle = {2015 IEEE International Conference on Big Data (Big Data)},
  doi = {10.1109/BigData.2015.7363835},
  isbn = {978-1-4799-9926-2},
  month = {oct},
  pages = {871--878},
  publisher = {IEEE},
  title = {{Using big data to study the link between human mobility and socio-economic development}},
  url = {http://ieeexplore.ieee.org/document/7363835/},
  year = {2015}
}
@article{Lenormand2015,
  abstract = {Human mobility has been traditionally studied using surveys that deliver snapshots of population displacement patterns. The growing accessibility to ICT information from portable digital media has recently opened the possibility of exploring human behavior at high spatio-temporal resolutions. Mobile phone records, geolocated tweets, check-ins from Foursquare or geotagged photos, have contributed to this purpose at different scales, from cities to countries, in different world areas. Many previous works lacked, however, details on the individuals' attributes such as age or gender. In this work, we analyze credit-card records from Barcelona and Madrid and by examining the geolocated credit-card transactions of individuals living in the two provinces, we find that the mobility patterns vary according to gender, age and occupation. Differences in distance traveled and travel purpose are observed between younger and older people, but, curiously, either between males and females of similar age. While mobility displays some generic features, here we show that sociodemographic characteristics play a relevant role and must be taken into account for mobility and epidemiological modelization.},
  archiveprefix = {arXiv},
  arxivid = {1411.7895},
  author = {Lenormand, Maxime and Louail, Thomas and Cant{\'{u}}-Ros, Oliva G. and Picornell, Miguel and Herranz, Ricardo and Arias, Juan Murillo and Barthelemy, Marc and Miguel, Maxi San and Ramasco, Jos{\'{e}} J.},
  doi = {10.1038/srep10075},
  eprint = {1411.7895},
  isbn = {2045-2322},
  issn = {20452322},
  journal = {Scientific Reports},
  month = {sep},
  number = {1},
  pages = {10075},
  pmid = {25993055},
  title = {{Influence of sociodemographics on human mobility}},
  url = {http://www.nature.com/articles/srep10075},
  volume = {5},
  year = {2015}
}
@article{Toole2015b,
  abstract = {Studies using massive, passively collected data from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion and organizational dynamics. More recently, these data have come tagged with geographical information, enabling studies of human mobility patterns and the science of cities. We combine these two pursuits and uncover reproducible mobility patterns among social contacts. First, we introduce measures of mobility similarity and predictability and measure them for populations of users in three large urban areas. We find individuals' visitations patterns are far more similar to and predictable by social contacts than strangers and that these measures are positively correlated with tie strength. Unsupervised clustering of hourly variations in mobility similarity identifies three categories of social ties and suggests geography is an important feature to contextualize social relationships. We find that the composition of a user's ego network in terms of the type of contacts they keep is correlated with mobility behaviour. Finally, we extend a popular mobility model to include movement choices based on social contacts and compare its ability to reproduce empirical measurements with two additional models of mobility.},
  author = {Toole, Jameson L. and Herrera-Yaq{\"{u}}e, Carlos and Schneider, Christian M. and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1098/rsif.2014.1128},
  issn = {17425662},
  journal = {Journal of the Royal Society Interface},
  keywords = {City science,Complex systems,Human mobility,Mobile phones,Networks},
  month = {feb},
  number = {105},
  pages = {20141128--20141128},
  pmid = {25716185},
  title = {{Coupling human mobility and social ties}},
  url = {http://rsif.royalsocietypublishing.org/cgi/doi/10.1098/rsif.2014.1128},
  volume = {12},
  year = {2015}
}
@article{SilvaLovera2015,
  abstract = {Urban sprawl in South America has for many decades been driven by the housing debate, with major impact on overall urban development. The impact of uncontrolled expansion has been social, economic and environmental degradation to high rates of poverty, poor services and transport. The presence of undeveloped areas within suburban landscapes, such as former infrastructural facilities, obsolete airports, and abandoned train stations, contribute to the impetus to reclaimed and revamped land. These spaces also trigger political aspirations for implementing better practices on "smart" growth, sustainable development and urban regeneration principles. A case in point is the former airport 'Aeropuerto Cerrillos' in Santiago, Chile, which closed in 2001 after years of decay; it intended to replace and host a large-scale urban project called 'Ciudad Parque Bicentenario'. This development is still incomplete and describes a series of pressures on a planning system traditionally adjusted to promote expansion confirming that urban sprawl is still an open agenda triggered by the presence of diverse unexpected urban gaps.},
  author = {{Silva Lovera}, Cristian Alejandro},
  journal = {Geoforum},
  doi = {10.1016/j.geoforum.2015.10.004},
  isbn = {0016-7185},
  issn = {00167185},
  keywords = {Infrastructural lands,Revamping processes,Urban sprawl},
  month = {dec},
  pages = {36--40},
  publisher = {Pergamon},
  title = {{Urban sprawl and infrastructural lands: Revamping internal spaces in Santiago de Chile}},
  url = {https://www.sciencedirect.com/science/article/pii/S0016718515302232},
  volume = {67},
  year = {2015}
}
@article{Lv2015,
  abstract = {Route classification based on trajectory data is one of the most essential issues for many location-aware applications. Most existing methods are based on physical locations of the trajectories. However, obtaining physical locations from mobile phones would incur extra cost (e.g. extra energy cost for using GPS). On the other hand, since every active mobile phone is connected to a nearby cell tower, cell-ids (i.e. identifiers of the connected cell towers) could be easily obtained without any additional hardware or network services. In this paper, a cell-id trajectory is a sequence of cell-ids with no regard to physical locations. We address the problem of route classification based on cell-id trajectory data. Specifically, we propose a novel similarity measure which explores the handoff patterns to capture the similarity between cell-id trajectories with no regard to physical locations. Then, based on the cell-id trajectory similarity measure, a clustering algorithm is used to discover potential route patterns from cell-id trajectories, and a nearest-neighbor classification algorithm is used to match current cell-id trajectories to route patterns. The performance of the proposed method is evaluated upon real-world cell-id trajectory dataset. The experimental results showed that our method outperforms state-of-the-art methods on cell-id trajectory clustering and cell-id route classification.},
  author = {Lv, Mingqi and Chen, Ling and Shen, Yanbin and Chen, Gencai},
  doi = {10.1016/j.knosys.2015.07.002},
  issn = {09507051},
  journal = {Knowledge-Based Systems},
  keywords = {Cell-id trajectory,Mobile phone user,Route classification,Similarity measure,Trajectory clustering},
  month = {nov},
  pages = {181--191},
  title = {{Measuring cell-id trajectory similarity for mobile phone route classification}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0950705115002464},
  volume = {89},
  year = {2015}
}
@article{Picornell2015,
  abstract = {Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users' mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.},
  author = {Picornell, Miguel and Ruiz, Tom{\'{a}}s and Lenormand, Maxime and Ramasco, Jos{\'{e}} J. and Dubernet, Thibaut and Fr{\'{i}}as-Mart{\'{i}}nez, Enrique},
  doi = {10.1007/s11116-015-9594-1},
  issn = {15729435},
  journal = {Transportation},
  keywords = {Activity-based modelling,Call Detail Record,Mobile phone,Social network,Travel behavior},
  month = {jul},
  number = {4},
  pages = {647--668},
  title = {{Exploring the potential of phone call data to characterize the relationship between social network and travel behavior}},
  url = {http://link.springer.com/10.1007/s11116-015-9594-1},
  volume = {42},
  year = {2015}
}
@article{Wang2015,
  abstract = {With the increasing popularity of mobile phones, large amounts of real and reliable mobile phone data are being generated every day. These mobile phone data represent the practical travel routes of users and imply the intelligence of them in selecting a suitable route. Usually, an experienced user knows which route is congested in a specified period of time but unblocked in another period of time. Moreover, a route used frequently and recently by a user is usually the suitable one to satisfy the user's needs. Adaptive control of thought-rational (ACT-R) is a computational cognitive architecture, which provides a good framework to understand the principles and mechanisms of information organization, retrieval and selection in human memory. In this paper, we employ ACT-R to model the process of selecting a suitable route of users. We propose a cognition-inspired route evaluation method to mine the intelligence of users in selecting a suitable route, evaluate the suitability of the routes, and then recommend an ordered list of routes for subscribers. Experiments show that it is effective and feasible to evaluate the suitability of the routes inspired by cognition.},
  author = {Wang, Hui and Huang, Jiajin and Zhou, Erzhong and Huang, Zhisheng and Zhong, Ning},
  doi = {10.1007/s11047-014-9479-9},
  issn = {15729796},
  journal = {Natural Computing},
  keywords = {Cognition-inspired evaluation,Mobile phone data,Routing service},
  month = {dec},
  number = {4},
  pages = {637--648},
  title = {{Cognition-inspired route evaluation using mobile phone data}},
  url = {http://link.springer.com/10.1007/s11047-014-9479-9},
  volume = {14},
  year = {2015}
}
@article{Secchi2015,
  abstract = {We analyze geo-referenced high-dimensional data describing the use over time of the mobile-phone network in the urban area of Milan, Italy. Aim of the analysis is to identify subregions of the metropolitan area of Milan sharing a similar pattern along time, and possibly related to activities taking place in specific locations and/or times within the city. To tackle this problem, we develop a non-parametric method for the analysis of spatially dependent functional data, named Bagging Voronoi Treelet analysis. This novel approach integrates the treelet decomposition with a proper treatment of spatial dependence, obtained through a Bagging Voronoi strategy. The latter relies on the aggregation of different replicates of the analysis, each involving a set of functional local representatives associated to random Voronoi-based neighborhoods covering the investigated area. Results clearly point out some interesting temporal patterns interpretable in terms of population density mobility (e.g., daily work activities in the tertiary district, leisure activities in residential areas in the evenings and in the weekend, commuters movements along the highways during rush hours, and localized mob concentrations related to occasional events). Moreover we perform simulation studies, aimed at investigating the properties and performances of the method, and whose description is available online as Supplementary material.},
  author = {Secchi, Piercesare and Vantini, Simone and Vitelli, Valeria},
  doi = {10.1007/s10260-014-0294-3},
  isbn = {1618-2510},
  issn = {1618-2510},
  journal = {Statistical Methods {\&} Applications},
  month = {jul},
  number = {2},
  pages = {279--300},
  title = {{Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan}},
  url = {http://link.springer.com/10.1007/s10260-014-0294-3},
  volume = {24},
  year = {2015}
}
@article{Zhao2016,
  abstract = {ABSTRACT: In recent years, call detail records (CDRs) have been widely used in human mobility research. Although CDRs are originally collected for billing purposes, the vast amount of digital footprints generated by calling and texting activities provide useful insights into population movement. However, can we fully trust CDRs given the uneven distribution of people's phone communication activities in space and time? In this article, we investigate this issue using a mobile phone location dataset collected from over one million subscribers in Shanghai, China. It includes CDRs ({\~{}}27{\%}) plus other cellphone-related logs (e.g., tower pings, cellular handovers) generated in a workday. We extract all CDRs into a separate dataset in order to compare human mobility patterns derived from CDRs vs. from the complete dataset. From an individual perspective, the effectiveness of CDRs in estimating three frequently used mobility indicators is evaluated. We find that CDRs tend to underestimate the total travel distance and the movement entropy, while they can provide a good estimate to the radius of gyration. In addition, we observe that the level of deviation is related to the ratio of CDRs in an individual's trajectory. From a collective perspective, we compare the outcomes of these two datasets in terms of the distance decay effect and urban community detection. The major differences are closely related to the habit of mobile phone usage in space and time. We believe that the event-triggered nature of CDRs does introduce a certain degree of bias in human mobility research and we suggest that researchers use caution to interpret results derived from CDR data.},
  author = {Zhao, Ziliang and Shaw, Shih Lung and Xu, Yang and Lu, Feng and Chen, Jie and Yin, Ling},
  doi = {10.1080/13658816.2015.1137298},
  isbn = {1365-8816},
  issn = {13623087},
  journal = {International Journal of Geographical Information Science},
  keywords = {Mobile phone location data,call detail records,human mobility,urban dynamics},
  month = {sep},
  number = {9},
  pages = {1738--1762},
  title = {{Understanding the bias of call detail records in human mobility research}},
  url = {http://www.tandfonline.com/doi/full/10.1080/13658816.2015.1137298},
  volume = {30},
  year = {2016}
}
@article{Barnett2016,
  abstract = {Macroscopic behavior of scientific and societal systems results from the aggregation of microscopic behaviors of their constituent elements, but connecting the macroscopic with the microscopic in human behavior has traditionally been difficult. Manifestations of homophily, the notion that individuals tend to interact with others who resemble them, have been observed in many small and intermediate size settings. However, whether this behavior translates to truly macroscopic levels, and what its consequences may be, remains unknown. Here, we use call detail records (CDRs) to examine the population dynamics and manifestations of social and spatial homophily at a macroscopic level among the residents of 23 states of India at the Kumbh Mela, a 3-month-long Hindu festival. We estimate that the festival was attended by 61 million people, making it the largest gathering in the history of humanity. While we find strong overall evidence for both types of homophily for residents of different states, participants from low-representation states show considerably stronger propensity for both social and spatial homophily than those from high-representation states. These manifestations of homophily are amplified on crowded days, such as the peak day of the festival, which we estimate was attended by 25 million people. Our findings confirm that homophily, which here likely arises from social influence, permeates all scales of human behavior.},
  archiveprefix = {arXiv},
  arxivid = {1605.06898},
  author = {Barnett, Ian and Khanna, Tarun and Onnela, Jukka Pekka},
  doi = {10.1371/journal.pone.0156794},
  eprint = {1605.06898},
  issn = {19326203},
  journal = {PLoS ONE},
  month = {may},
  number = {6},
  title = {{Social and spatial clustering of people at humanity's largest gathering}},
  url = {http://arxiv.org/abs/1605.06898 http://dx.doi.org/10.1371/journal.pone.0156794},
  volume = {11},
  year = {2016}
}
@article{Phone2016,
  author = {Phone, Mobile and Reveal, Records and Gathering, Largest and Phone, Mobile and Reveal, Records and Gathering, Largest},
  pages = {1--5},
  title = {{7/1/2016 Mobile Phone Records Reveal Largest Gathering in the History of Humanity}},
  url = {https://www.technologyreview.com/s/601624/mobile-phone-records-reveal-largest-gathering-in-the-history-of-humanity/},
  year = {2016}
}
@article{Decuyper2016,
  abstract = {Mobile phone data have been extensively used in the recent years to study social behavior. However, most of these studies are based on only partial data whose coverage is limited both in space and time. In this paper, we point to an observation that the bias due to the limited coverage in time may have an important influence on the results of the analyses performed. In particular, we observe significant differences, both qualitatively and quantitatively, in the degree distribution of the network, depending on the way the dataset is pre-processed and we present a possible explanation for the emergence of Double Pareto LogNormal (DPLN) degree distributions in temporal data.},
  archiveprefix = {arXiv},
  arxivid = {1609.09413},
  author = {Decuyper, Adeline and Browet, Arnaud and Traag, Vincent and Blondel, Vincent D. and Delvenne, Jean-Charles},
  eprint = {1609.09413},
  file = {::},
  month = {sep},
  title = {{Clean up or mess up: the effect of sampling biases on measurements of degree distributions in mobile phone datasets}},
  url = {http://arxiv.org/abs/1609.09413},
  year = {2016}
}
@article{Leng2016,
  abstract = {Tourism has been an increasingly important factor in global economy, society and environment, accounting for a significant share of GDP and labor force. Policy and research on tourism traditionally rely on surveys and economic datasets, which are based on small samples and depict tourism dynamics at low spatial and temporal granularity. Anonymous call detail records (CDRs) are a novel source of data, showing enormous potential in areas of high societal value: such as epidemics, poverty, and urban development. This study demonstrates the added value of using CDRs for the formulation, analysis and evaluation of tourism strategies, at the national and local levels. In the context of the European country of Andorra, we use CDRs to evaluate marketing strategies in tourism, understand tourists' experiences, and evaluate revenues and externalities generated by touristic events. We do this by extracting novel indicators in high spatial and temporal resolutions, such as tourist flows per country of origin, flows of new tourists, tourist revisits, tourist externalities on transportation congestion, spatial distribution, economic impact, and profiling of tourist interests. We exemplify the use of these indicators for the planning and evaluation of high impact touristic events, such as cultural festivals and sports competitions.},
  archiveprefix = {arXiv},
  arxivid = {1610.08342},
  author = {Leng, Yan and Noriega, Alejandro and Pentland, Alex 'Sandy' and Winder, Ira and Lutz, Nina and Alonso, Luis},
  eprint = {1610.08342},
  file = {::},
  month = {oct},
  title = {{Analysis of Tourism Dynamics and Special Events through Mobile Phone Metadata}},
  url = {http://arxiv.org/abs/1610.08342},
  year = {2016}
}
@article{Sundsoy2016,
  abstract = {This study provides the first confirmation that individual employment status can be predicted from standard mobile phone network logs externally validated with household survey data. Individual welfare and households' vulnerability to shocks are intimately connected to employment status and professions of household breadwinners. At a societal level unemployment is an important indicator of the performance of an economy. By deriving a broad set of novel mobile phone network indicators reflecting users' financial, social and mobility patterns we show how machine learning models can be used to predict 18 categories of profession in a South-Asian developing country. The model predicts individual unemployment status with 70.4{\%} accuracy. We further show how unemployment can be aggregated from individual level and mapped geographically at cell tower resolution, providing a promising approach to map labor market economic indicators, and the distribution of economic productivity and vulnerability between censuses, especially in heterogeneous urban areas. The method also provides a promising approach to support data collection on vulnerable populations, which are frequently under-represented in official surveys.},
  journal = {{arXiv}},
  archiveprefix = {arXiv},
  arxivid = {1612.03870},
  author = {Sunds{\o}y, P{\aa}l and Bjelland, Johannes and Reme, Bj{\o}rn-Atle and Jahani, Eaman and Wetter, Erik and Bengtsson, Linus},
  eprint = {1612.03870},
  file = {::},
  keywords = {Big-Data Development,machine learning,mobile phone metadata,profession,socio- economic indicators,unemployment},
  month = {dec},
  pages = {1--6},
  title = {{Estimating individual employment status using mobile phone network data}},
  url = {http://arxiv.org/abs/1612.03870},
  year = {2016}
}
@article{DeMonasterio2017,
  abstract = {We use mobile phone records for the analysis of mobility patterns and the detection of possible risk zones of Chagas disease in two Latin American countries. We show that geolocalized call records are rich in social and individual information, which can be used to infer whether an individual has lived in an endemic area. We present two case studies, in Argentina and in Mexico, using data provided by mobile phone companies from each country. The risk maps that we generate can be used by health campaign managers to target specific areas and allocate resources more effectively.},
  archiveprefix = {arXiv},
  arxivid = {1707.01149},
  author = {{De Monasterio}, Juan and Salles, Alejo and Lang, Carolina and Weinberg, Diego and Minnoni, Martin and Travizano, Matias and Sarraute, Carlos},
  doi = {10.1109/ASONAM.2016.7752298},
  eprint = {1707.01149},
  file = {::},
  isbn = {9781509028467},
  journal = {Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016},
  month = {jul},
  pages = {607--612},
  title = {{Analyzing the spread of chagas disease with mobile phone data}},
  url = {http://arxiv.org/abs/1707.01149 http://dx.doi.org/10.1109/ASONAM.2016.7752298},
  year = {2016}
}
@inproceedings{Sekimoto2016,
  abstract = {{\textcopyright} 2016 ACM.Recently, an understanding of mass movement in urban areas immediately after large disasters, such as the Great East Japan Earthquake (GEJE), has been needed. In particular, mobile phone data is available as time-varying data. However, much more detailed movement that is based on network flow instead of aggregated data is needed for appropriate rescue on a real-Time basis. Hence, our research aims to estimate real-Time human movement during large disasters from several kinds of mobile phone data. In this paper, we simulate the movement of people in the Tokyo metropolitan area in a large disaster situation and obtain several kinds of fragmentary movement observation data from mobile phones. Our approach is to use data assimilation techniques combining with simulation of population movement and observation data. The experimental results confirm that the improvement in accuracy depends on the observation data quality using sensitivity analysis and data processing speed to satisfy each condition for real-Time estimation.},
  address = {New York, New York, USA},
  author = {Sekimoto, Yoshihide and Sudo, Akihito and Kashiyama, Takehiro and Seto, Toshikazu and Hayashi, Hideki and Asahara, Akinori and Ishizuka, Hiroki and Nishiyama, Satoshi},
  booktitle = {Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16},
  doi = {10.1145/2968219.2968421},
  isbn = {9781450344623},
  keywords = {GIS,data assimilation,disaster activity,engineering,human safety,mobile phone data,multiagent systems,people mass movement,real time,sociology,spatial databases},
  pages = {1426--1434},
  publisher = {ACM Press},
  title = {{Real-time people movement estimation in large disasters from several kinds of mobile phone data}},
  url = {http://dl.acm.org/citation.cfm?doid=2968219.2968421},
  year = {2016}
}
@inproceedings{Reed2016,
  abstract = {{\textcopyright} Copyright 2016 ACM.We explore the extent to which gender disparities in Pak- istan are reected in the anonymized mobile phone logs of millions of Pakistani residents. Our analysis uses data capturing the communications behavior of several million individuals, for whom we observe the gender, but no additional demographic or personally identifying information. Here, we focus on validating aggregate regional patterns, correlating metrics derived from the mobile phone logs with socioeconomic statistics collected from more traditional sources. In these preliminary results, we observe a statistically significant relationship between districts with relatively high rates of female mobile phone penetration and districts that report high levels of gender parity in traditional surveys. However, this relationship is not uniform, and less developed regions exhibit a weaker correlation. We interpret these findings as suggestive evidence that such data can provide a novel perspective on gender dynamics in developing countries.},
  address = {New York, New York, USA},
  author = {Reed, Philip J. and Khan, Muhammad Raza and Blumenstock, Joshua},
  booktitle = {Proc. of the Eighth International Conference on Information and Communication Technologies and Development - ICTD '16},
  doi = {10.1145/2909609.2909632},
  isbn = {9781450343060},
  keywords = {Gender,Pakistan,big data and development,call detail records,data science,mobile phones},
  pages = {1--4},
  publisher = {ACM Press},
  title = {{Observing gender dynamics and disparities with mobile phone metadata}},
  url = {http://dl.acm.org/citation.cfm?doid=2909609.2909632},
  year = {2016}
}
@book{InstituteofElectricalandElectronicsEngineers2016,
  abstract = {"FAB 2016, FOSINT-SI 2016, HIBIBI 2016"--PDF cover. IEEE Catalog Number: CFP1634H-ART; IEEE Catalog Number: CFP1634H-USB. Annotation The conference will consider papers in all areas of social networks and mining In recent years, social network research has advanced significantly the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution This has led to a rising prominence of SNAM in academia, politics, homeland security and business This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding.},
  author = {{Institute of Electrical and Electronics Engineers}, Michelle and Suthers, Daniel D.},
  booktitle = {Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining},
  isbn = {9781509028467},
  pages = {876--879},
  publisher = {IEEE Press},
  title = {{Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining : ASONAM 2016 : San Francisco, CA, USA, August 18-21, 2016}},
  url = {https://dl.acm.org/citation.cfm?id=3192587},
  year = {2016}
}
@inproceedings{Islam2016,
  abstract = {Mobile phones are seen as a means for social and economic progress in$\backslash$nrural and remote areas of developing countries. In Bangladesh the$\backslash$navailability and use of information and communication technology (ICT),$\backslash$nparticularly mobile phones, is thought to have accelerated the$\backslash$ndevelopment of women in the rural population by creating the possibility$\backslash$nof a wider connection. Using qualitative and quantitative methods for$\backslash$ndata collection, this research has investigated the impact of mobile$\backslash$nphone use by women with particular emphasis on opportunities in health,$\backslash$neducation and livelihood. A sample of 99 women from three rural villages$\backslash$nin Bangladesh showed that mobile phones provide easy access to health$\backslash$nrelated services. Although impact on facilitating girls' education$\backslash$nappears to be limited, mobile phones have an indirect effect in ensuring$\backslash$nsecurity for girls. Respondents confirmed that their overall living$\backslash$nstandards have improved due to access to information on economic and$\backslash$nincome earning opportunities. These rural women also feel independent$\backslash$nand empowered by access to a mobile phone. It can be argued that mobile$\backslash$nphone technology can facilitate improvements in the living standards of$\backslash$nrural women, which contribute to their personal development. Finally,$\backslash$nthe paper suggests that wide and innovative utilization of ICT is needed$\backslash$nto accelerate development of women in the rural population with the help$\backslash$nof low- cost mobile phone technology.},
  address = {New York, New York, USA},
  author = {Islam, Mohd Kamrul and Slack, Frances},
  booktitle = {Proceedings of the 9th International Conference on Theory and Practice of Electronic Governance  - ICEGOV '15-16},
  doi = {10.1145/2910019.2910074},
  isbn = {9781450336406},
  keywords = {Access and Accessibility,Information Sharing,Mobile Phones,Rural Population,Women in Bangladesh},
  pages = {75--84},
  pmid = {2910074},
  publisher = {ACM Press},
  title = {{Women in Rural Bangladesh}},
  url = {http://dl.acm.org/citation.cfm?doid=2910019.2910074},
  year = {2016}
}
@inproceedings{Kaewnoi2016,
  address = {New York, New York, USA},
  author = {Kaewnoi, Nuttapong and Suntiparadonkul, Narida and Phithakkitnukoon, Santi and Smoreda, Zbibniew},
  booktitle = {Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16},
  doi = {10.1145/2968219.2968413},
  isbn = {9781450344623},
  keywords = {data visualization,mobile usage,urban flow},
  pages = {1358--1362},
  publisher = {ACM Press},
  title = {{Visualizing mobile phone usage for exploratory analysis}},
  url = {http://dl.acm.org/citation.cfm?doid=2968219.2968413},
  year = {2016}
}
@inproceedings{DeNadai2016,
  abstract = {The Death and Life of Great American Cities was written in 1961 and is now one of the most influential book in city planning. In it, Jane Jacobs proposed four conditions that promote life in a city. However, these conditions have not been empirically tested until recently. This is mainly because it is hard to collect data about "city life". The city of Seoul recently collected pedestrian activity through surveys at an unprecedented scale, with an effort spanning more than a decade, allowing researchers to conduct the first study successfully testing Jacobs's conditions. In this paper, we identify a valuable alternative to the lengthy and costly collection of activity survey data: mobile phone data. We extract human activity from such data, collect land use and socio-demographic information from the Italian Census and Open Street Map, and test the four conditions in six Italian cities. Although these cities are very different from the places for which Jacobs's conditions were spelled out (i.e., great American cities) and from the places in which they were recently tested (i.e., the Asian city of Seoul), we find those conditions to be indeed associated with urban life in Italy as well. Our methodology promises to have a great impact on urban studies, not least because, if replicated, it will make it possible to test Jacobs's theories at scale.},
  address = {New York, New York, USA},
  archiveprefix = {arXiv},
  arxivid = {1603.04012},
  author = {{De Nadai}, Marco and Staiano, Jacopo and Larcher, Roberto and Sebe, Nicu and Quercia, Daniele and Lepri, Bruno},
  booktitle = {Proceedings of the 25th International Conference on World Wide Web - WWW '16},
  doi = {10.1145/2872427.2883084},
  eprint = {1603.04012},
  isbn = {9781450341431},
  keywords = {cities,mobile phone data,open data,urban informatics},
  pages = {413--423},
  publisher = {ACM Press},
  title = {{The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective}},
  url = {http://arxiv.org/abs/1603.04012{\%}0Ahttp://dx.doi.org/10.1145/2872427.2883084},
  year = {2016}
}
@inproceedings{Hoan2016,
  abstract = {The Capability Approach, as developed by Amartya Sen, has been criticized for an overly individualistic approach, while simultaneously being re-framed in alignment with the dominant social structure. We situate individual agency within the frame of social power structures, examining agency and empowerment gained by mobile phone usage from 26 Vietnamese foreign brides in Singapore. We use an intersectionality perspective from gender studies to find that, while facing multiple grounds of discrimination from the dominant group, the women constantly negotiate at the intersections of gender, ethnicity and social class, leading to two active strategies for positive well-being and empowerment: Essentialization of gender and Aspiration. The mobile phone was found to be an active agent in facilitating their aspiration for individual changes, autonomy, and more powerful decision making roles in domestic and social domains - A variety of communicative practices developed their capabilities. On the other hand, Mobiles also mediated the enactment and practices of the foreign brides' essential beliefs of their own idealized femininity and traditional gender roles, in contrast with the dominant development discourse of women's empowerment. The socio-cultural contexts influencing processes of technological appropriation is discussed from the perspective of development, particularly re-framing Western notions of gender equality within the agentic framework. {\textcopyright} Copyright 2016 ACM.},
  address = {New York, New York, USA},
  author = {Hoan, Nguyen Thi and Chib, Arul and Mahalingham, Ram},
  booktitle = {Proceedings of the Eighth International Conference on Information and Communication Technologies and Development - ICTD '16},
  doi = {10.1145/2909609.2909671},
  isbn = {9781450343060},
  keywords = {ICT4D,gender equality,mobile phones,restricted agency,women's empowerment},
  pages = {1--10},
  publisher = {ACM Press},
  title = {{Mobile phones and Gender Empowerment}},
  url = {http://dl.acm.org/citation.cfm?doid=2909609.2909671},
  year = {2016}
}
@inproceedings{Mao2016,
  abstract = {In the context of Smart Africa Initiative, we present a method to infer multiple land use in Africa. Such information is usually scarce in developing countries due to the constrained resources. Timely land use information is a critical input to smart urban planning that improves efficiency for the public to access to resources. The mobile phone usage is almost universal, which creates a valuable data source for land use inference. In this paper, we demonstrate that the temporal mobile phone call pattern and call network features can be combined to infer tencategory land use including residential, commercial-industrial/office, commercial-business/ retail/leisure, high- and low- density commercial, high- and low density residential, mixed land use areas as well as com- mercial and residential hubs of the city. In low income countries where land use surveys are rare, our approach create an alternative for measuring land use. {\textcopyright} 2016 ACM.},
  address = {New York, New York, USA},
  author = {Mao, Huina and Thakur, Gautam and Bhaduri, Budhendra},
  booktitle = {Proceedings of the 2nd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics - UrbanGIS '16},
  doi = {10.1145/3007540.3007549},
  isbn = {9781450345835},
  keywords = {big data,mobile phone data,multi-category land use classification,smart cities},
  pages = {1--6},
  publisher = {ACM Press},
  title = {{Exploiting mobile phone data for multi-category land use classification in Africa}},
  url = {http://dl.acm.org/citation.cfm?doid=3007540.3007549},
  year = {2016}
}
@inproceedings{Smith-Clarke2016,
  abstract = {Within the remit of 'Data for Development' there have been a number of promising recent works that investigate the use of mobile phone Call Detail Records (CDRs) to estimate the spatial distribution of poverty or socio-economic status. The methods being developed have the potential to offer immense value to organisations and agencies who currently struggle to identify the poorest parts of a country, due to the lack of reliable and up to date survey data in certain parts of the world. However, the results of this research have thus far only been presented in isolation rather than in comparison to any alternative approach or benchmark. Consequently, the true practical value of these methods remains unknown. Here, we seek to allay this shortcoming, by proposing two baseline poverty estimators grounded on concrete usage sce-narios: one that exploits correlation with population density only, to be used when no poverty data exists at all; and one that also exploits spatial autocorrelation, to be used when poverty data has been collected for a few regions within a country. We then compare the predictive performance of these baseline models with models that also include features derived from CDRs, so to establish their real added value. We present extensive analysis of the performance of all these models on data acquired for two developing countries – Sene-gal and Ivory Coast. Our results reveal that CDR-based models do provide more accurate estimates in most cases; however, the improvement is modest and more significant when estimating (extreme) poverty intensity rates rather than mean wealth.},
  address = {New York, New York, USA},
  author = {Smith-Clarke, Chris and Capra, Licia},
  booktitle = {Proceedings of the 25th International Conference on World Wide Web - WWW '16},
  doi = {10.1145/2872427.2883076},
  isbn = {9781450341431},
  keywords = {call detail records,data for development,mobile phone data,poverty},
  pages = {425--434},
  publisher = {ACM Press},
  title = {{Beyond the Baseline}},
  url = {http://dl.acm.org/citation.cfm?doid=2872427.2883076},
  year = {2016}
}
@article{Wyche2016,
  abstract = {This article provides a detailed analysis of rural Kenyan women and their interactions with the products and services of Safaricom Ltd., Kenya's dominant mobile network provider. The amplification theory of tech-nology offers a framework for analyzing our data, and we find that differential motivation and capacity are mechanisms that appear to benefit the network provider, while disadvantaging rural mobile phone owners. In particular, the design of Safaricom's airtime scratch cards and mobile services does not support rural users' capabilities. Our analysis suggests that technologists consider their ongoing responsibilities for technologies they built yesterday—that is, they should address problems inherent in the current design of mobile-phone interfaces. We offer practical recommendations on how to do this, and ask HCI/ICTD researchers and prac-titioners to more carefully consider how overlooking corporate power structures and their impact on mobile phone use amplifies social inequality.},
  author = {Wyche, Susan and Simiyu, Nightingale and Othieno, Martha E.},
  doi = {10.1145/2911982},
  isbn = {1073-0516},
  issn = {10730516},
  journal = {ACM Transactions on Computer-Human Interaction},
  keywords = {Amplification theory,HCI4D,ICTD,Kenya,M-Pesa,design,mobile phones,rural,women},
  month = {jun},
  number = {3},
  pages = {1--19},
  publisher = {ACM},
  title = {{Mobile Phones as Amplifiers of Social Inequality among Rural Kenyan Women}},
  url = {http://dl.acm.org/citation.cfm?doid=2952594.2911982},
  volume = {23},
  year = {2016}
}
@article{Brdar2015,
  abstract = {An increasing amount of geo-referenced mobile phone data enables the identification of behavioral patterns, habits and movements of people. With this data, we can extract the knowledge potentially useful for many applications including the one tackled in this study - understanding spatial variation of epidemics. We explored the datasets collected by a cell phone service provider and linked them to spatial HIV prevalence rates estimated from publicly available surveys. For that purpose, 224 features were extracted from mobility and connectivity traces and related to the level of HIV epidemic in 50 Ivory Coast departments. By means of regression models, we evaluated predictive ability of extracted features. Several models predicted HIV prevalence that are highly correlated ({\textgreater}0.7) with actual values. Through contribution analysis we identified key elements that correlate with the rate of infections and could serve as a proxy for epidemic monitoring. Our findings indicate that night connectivity and activity, spatial area covered by users and overall migrations are strongly linked to HIV. By visualizing the communication and mobility flows, we strived to explain the spatial structure of epidemics. We discovered that strong ties and hubs in communication and mobility align with HIV hot spots.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1503.06575v1},
  author = {Brdar, Sanja and Gavri{\'{c}}, Katarina and {\'{C}}ulibrk, Dubravko and Crnojevi{\'{c}}, Vladimir},
  doi = {10.1038/srep19342},
  eprint = {arXiv:1503.06575v1},
  file = {::},
  isbn = {2045-2322},
  issn = {20452322},
  journal = {Scientific Reports},
  month = {mar},
  pmid = {26758042},
  title = {{Unveiling Spatial Epidemiology of HIV with Mobile Phone Data}},
  url = {http://arxiv.org/abs/1503.06575},
  volume = {6},
  year = {2016}
}
@article{DeNadai2016a,
  abstract = {The Death and Life of Great American Cities was written in 1961 and is now one of the most influential book in city planning. In it, Jane Jacobs proposed four conditions that promote life in a city. However, these conditions have not been empirically tested until recently. This is mainly because it is hard to collect data about "city life". The city of Seoul recently collected pedestrian activity through surveys at an unprecedented scale, with an effort spanning more than a decade, allowing researchers to conduct the first study successfully testing Jacobs's conditions. In this paper, we identify a valuable alternative to the lengthy and costly collection of activity survey data: mobile phone data. We extract human activity from such data, collect land use and socio-demographic information from the Italian Census and Open Street Map, and test the four conditions in six Italian cities. Although these cities are very different from the places for which Jacobs's conditions were spelled out (i.e., great American cities) and from the places in which they were recently tested (i.e., the Asian city of Seoul), we find those conditions to be indeed associated with urban life in Italy as well. Our methodology promises to have a great impact on urban studies, not least because, if replicated, it will make it possible to test Jacobs's theories at scale.},
  archiveprefix = {arXiv},
  arxivid = {1603.04012},
  author = {{De Nadai}, Marco and Staiano, Jacopo and Larcher, Roberto and Sebe, Nicu and Quercia, Daniele and Lepri, Bruno},
  doi = {10.1145/2872427.2883084},
  eprint = {1603.04012},
  file = {::},
  isbn = {9781450341431},
  month = {mar},
  title = {{The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective}},
  url = {http://arxiv.org/abs/1603.04012{\%}0Ahttp://dx.doi.org/10.1145/2872427.2883084},
  year = {2016}
}
@techreport{Buckee2016,
  abstract = {We outline the constraints faced by operators when deciding to share de-identified data with researchers or policy makers. We describe a conservative approach that we have taken to harness the value of CDRs for infectious disease epidemiology while ensuring that identification of individuals is impossible. We believe this approach serves as a useful and highly conservative model for productive partnerships between mobile operators, researchers, and public health practitioners.},
  archiveprefix = {arXiv},
  number = {1606.00864},
  institution = {arXiv},
  author = {Buckee, Caroline O. and Eng{\o}-Monsen, Kenth},
  eprint = {1606.00864},
  file = {::},
  month = {jun},
  title = {{Mobile phone data for public health: towards data-sharing solutions that protect individual privacy and national security}},
  url = {http://arxiv.org/abs/1606.00864},
  year = {2016}
}
@inproceedings{EspinNoboa2016,
  abstract = {Nowadays, human movement in urban spaces can be traced digitally in many cases. It can be observed that movement patterns are not constant, but vary across time and space. In this work, we characterize such spatio--temporal patterns with an innovative combination of two separate approaches that have been utilized for studying human mobility in the past. First, by using non--negative tensor factorization (NTF), we are able to cluster human behavior based on spatio--temporal dimensions. Second, for understanding these clusters, we propose to use HypTrails, a Bayesian approach for expressing and comparing hypotheses about human trails. To formalize hypotheses we utilize data that is publicly available on the Web, namely Foursquare data and census data provided by an open data platform. By applying this combination of approaches to taxi data in Manhattan, we can discover and characterize different patterns in human mobility that cannot be identified in a collective analysis. As one example, we can find a group of taxi rides that end at locations with a high number of party venues (according to Foursquare) on weekend nights. Overall, our work demonstrates that human mobility is not one--dimensional but rather contains different facets both in time and space which we explain by utilizing online data. The findings of this paper argue for a more fine--grained analysis of human mobility in order to make more informed decisions for e.g., enhancing urban structures, tailored traffic control and location--based recommender systems.},
  address = {New York, New York, USA},
  archiveprefix = {arXiv},
  arxivid = {1601.05274},
  author = {Esp$\backslash$'$\backslash$in-Noboa, Lisette and Lemmerich, Florian and Singer, Philipp and Strohmaier, Markus},
  booktitle = {Proceedings of the 6th International Workshop on Location and the Web},
  doi = {10.1145/2872518.2890468},
  eprint = {1601.05274},
  isbn = {9781450341448},
  keywords = {Human Mobility; Tensor Factorization; HypTrails},
  pages = {186--194},
  publisher = {ACM Press},
  title = {{Discovering and Explaining Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data}},
  url = {http://dl.acm.org/citation.cfm?doid=2872518.2890468},
  year = {2016}
}
@book{IEEESystems,
  abstract = {Some issues have also a distinctive theme title.},
  author = {The, O F and Interdisciplinary, International},
  doi = {10.1016/S0022-3182(86)80123-6},
  isbn = {9789966261045},
  issn = {00223182},
  title = {{Conference proceedings}},
  year = {2016}
}
@incollection{Dashdorj2016,
  abstract = {The enormous amount of recently available mobile phone data is providing unprecedented direct measurements of human behavior. Early recognition and prediction of behavioral patterns are of great importance in many societal applications like urban planning, transportation optimization, and health-care. Understanding the relationships between human behaviors and location's context is an emerging interest for understanding human-environmental dynamics. Growing availability of Web 2.0, i.e. the increasing amount of websites with mainly user created content and social platforms opens up an opportunity to study such location's contexts. This paper investigates relationships existing between human behavior and location context, by analyzing log mobile phone data records. First an advanced approach to categorize areas in a city based on the presence and distribution of categories of human activity (e.g., eating, working, and shopping) found across the areas, is proposed. The proposed classification is then evaluated through its comparison with the patterns of temporal variation of mobile phone activity and applying machine learning techniques to predict a timeline type of communication activity in a given location based on the knowledge of the obtained category vs. land-use type of the locations areas. The proposed classification turns out to be more consistent with the temporal variation of human communication activity, being a better predictor for those compared to the official land use classification.},
  archiveprefix = {arXiv},
  arxivid = {1510.02995},
  author = {Dashdorj, Zolzaya and Sobolevsky, Stanislav},
  booktitle = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-662-53416-8_10},
  eprint = {1510.02995},
  isbn = {9783662534151},
  issn = {16113349},
  keywords = {Big data,Cell phone data records,Clustering algorithms,Geospatial data,Human activity recognition,Human behavior,Knowledge management,Land-use,Supervised learning algorithms},
  pages = {159--176},
  title = {{Characterization of behavioral patterns exploiting description of geographical areas}},
  url = {http://link.springer.com/10.1007/978-3-662-53416-8{\_}10},
  volume = {9860 LNCS},
  year = {2016}
}
@article{Wang2016,
  abstract = {Dynamic pricing has been used extensively in specific markets for many years but recent years have seen an interest in the utilization of this approach for the deployment of novel and attractive tariff structures for mobile communication services. This paper describes the development and operation of an agent based model (ABM) for subscriber behavior in a dynamically priced mobile telephony network. The design of the ABM was based on an analysis of real call detail records recorded in a Uganda mobile telephony network in which dynamic pricing was deployed. The ABM includes components which simulate subscriber calling behavior, mobility within the network and social linkages. Using this model, this paper reports on an investigation of a number of alternative strategies for the dynamic pricing algorithm which indicate that the network operator will likely experience revenue losses ranging from a 5 {\%}, when the pricing algorithm is based on offering high value subscriber cohort enhanced random discounts compared to a lower value subscriber cohort, to 30 {\%}, when the priding algorithm results in the discount on offer in a cell being inversely proportional to the contemporary cell load. Additionally, the model appears to suggest that the use of optimization algorithms to control the level of discount offered in cells would likely result in discount simply converging to a “no-discount” scenario. Finally, commentary is offered on additional factors which need to be considered when interpreting the results of this work such as the impact of subscriber churn on the size of the subscriber base and the technical and marketing challenges of deploying the various dynamic pricing algorithms which have been investigated.},
  author = {Wang, Han and Fay, Damien and Brown, Kenneth N. and Kilmartin, Liam},
  doi = {10.1007/s11235-015-0106-6},
  issn = {15729451},
  journal = {Telecommunication Systems},
  keywords = {Agent-based model,Dynamic pricing,Mobile network services,Revenue optimization},
  month = {aug},
  number = {4},
  pages = {711--734},
  title = {{Modelling revenue generation in a dynamically priced mobile telephony service}},
  url = {http://link.springer.com/10.1007/s11235-015-0106-6},
  volume = {62},
  year = {2016}
}
@incollection{Truica2018,
  author = {Bedi, Punam and Sharma, Chhavi},
  booktitle = {Wiley Int. Rev. Data Min. and Knowl. Disc.},
  doi = {10.1002/widm.1178},
  issn = {1942-4787},
  number = {3},
  pages = {115--135},
  title = {{Community Detection in Social Networks}},
  url = {https://doi.org/10.1002/widm.1178},
  volume = {6},
  year = {2016}
}
@article{McCallum2016,
  abstract = {Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already been proven to effectively aid in humanitarian response and recovery. However, while ex-ante technologies are increasingly utilized to collect information on exposure, efforts directed towards assessing and monitoring hazards and vulnerability remain limited. Hazard model validation and social vulnerability assessment deserve particular attention. New technologies offer great potential for engaging people and facilitating the coproduction of knowledge.},
  author = {McCallum, Ian and Liu, Wei and See, Linda and Mechler, Reinhard and Keating, Adriana and Hochrainer-Stigler, Stefan and Mochizuki, Junko and Fritz, Steffen and Dugar, Sumit and Arestegui, Miguel and Szoenyi, Michael and Bayas, Juan Carlos Laso and Burek, Peter and French, Adam and Moorthy, Inian},
  doi = {10.1007/s13753-016-0086-5},
  isbn = {2192-6395},
  issn = {20950055},
  journal = {International Journal of Disaster Risk Science},
  keywords = {Crowdsourcing,Disaster risk reduction,Flood resilience,Social media,Volunteered geographic information (VGI)},
  month = {jun},
  number = {2},
  pages = {198--204},
  title = {{Technologies to Support Community Flood Disaster Risk Reduction}},
  url = {http://link.springer.com/10.1007/s13753-016-0086-5},
  volume = {7},
  year = {2016}
}
@article{Lu2016,
  abstract = {Large-scale data from digital infrastructure, like mobile phone networks, provides rich information on the behavior of millions of people in areas affected by climate stress. Using anonymized data on mobility and calling behavior from 5.1 million Grameenphone users in Barisal Division and Chittagong District, Bangladesh, we investigate the effect of Cyclone Mahasen, which struck Barisal and Chittagong in May 2013. We characterize spatiotemporal patterns and anomalies in calling frequency, mobile recharges, and population movements before, during and after the cyclone. While it was originally anticipated that the analysis might detect mass evacuations and displacement from coastal areas in the weeks following the storm, no evidence was found to suggest any permanent changes in population distributions. We detect anomalous patterns of mobility both around the time of early warning messages and the storm's landfall, showing where and when mobility occurred as well as its characteristics.)},
  author = {Lu, Xin and Wrathall, David J. and Sunds{\o}y, P{\aa}l Roe and Nadiruzzaman, Md and Wetter, Erik and Iqbal, Asif and Qureshi, Taimur and Tatem, Andrew J. and Canright, Geoffrey S. and Eng{\o}-Monsen, Kenth and Bengtsson, Linus},
  doi = {10.1007/s10584-016-1753-7},
  issn = {15731480},
  journal = {Climatic Change},
  keywords = {Anomaly detection,Climate change adaptation,Disaster risk,Migration,Mobile network data,Resilience},
  month = {oct},
  number = {3-4},
  pages = {505--519},
  title = {{Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen}},
  url = {http://link.springer.com/10.1007/s10584-016-1753-7},
  volume = {138},
  year = {2016}
}
@incollection{Lepri2017,
  abstract = {The unprecedented availability of large-scale human behavioral data is profoundly changing the world we live in. Researchers, companies, governments, financial institutions, non-governmental organizations and also citizen groups are actively experimenting, innovating and adapting algorithmic decision-making tools to understand global patterns of human behavior and provide decision support to tackle problems of societal importance. In this chapter, we focus our attention on social good decision-making algorithms, that is algorithms strongly influencing decision-making and resource optimization of public goods, such as public health, safety, access to finance and fair employment. Through an analysis of specific use cases and approaches, we highlight both the positive opportunities that are created through data-driven algorithmic decision-making, and the potential negative consequences that practitioners should be aware of and address in order to truly realize the potential of this emergent field. We elaborate on the need for these algorithms to provide transparency and accountability, preserve privacy and be tested and evaluated in context, by means of living lab approaches involving citizens. Finally, we turn to the requirements which would make it possible to leverage the predictive power of data-driven human behavior analysis while ensuring transparency, accountability, and civic participation.},
  archiveprefix = {arXiv},
  arxivid = {1612.00323},
  author = {Lepri, Bruno and Staiano, Jacopo and Sangokoya, David and Letouz{\'{e}}, Emmanuel and Oliver, Nuria},
  doi = {10.1007/978-3-319-54024-5_1},
  eprint = {1612.00323},
  isbn = {2197-6503},
  pages = {3--24},
  title = {{The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good}},
  url = {http://arxiv.org/abs/1612.00323},
  year = {2016}
}
@article{Lai2016,
  abstract = {In recent years, cellular floating vehicle data (CFVD) has been a popular traffic information estimation technique to analyze cellular network data and to provide real-time traffic information with higher coverage and lower cost. Therefore, this study proposes vehicle positioning and speed estimation methods to capture CFVD and to track mobile stations (MS) for intelligent transportation systems (ITS). Three features of CFVD, which include the IDs, sequence, and cell dwell time of connected cells from the signals of MS communication, are extracted and analyzed. The feature of sequence can be used to judge urban road direction, and the feature of cell dwell time can be applied to discriminate proximal urban roads. The experiment results show the accuracy of the proposed vehicle positioning method, which is 100{\%} better than other popular machine learning methods (e.g., naive Bayes classification, decision tree, support vector machine, and back-propagation neural network). Furthermore, the accuracy of the proposed method with all features (i.e., the IDs, sequence, and cell dwell time of connected cells) is 83.81{\%} for speed estimation. Therefore, the proposed methods based on CFVD are suitable for detecting the status of urban road traffic},
  author = {Lai, Wei-Kuang and Kuo, Ting-Huan},
  doi = {10.3390/ijgi5100181},
  issn = {2220-9964},
  journal = {ISPRS International Journal of Geo-Information},
  month = {oct},
  number = {10},
  pages = {181},
  title = {{Vehicle Positioning and Speed Estimation Based on Cellular Network Signals for Urban Roads}},
  url = {http://www.mdpi.com/2220-9964/5/10/181},
  volume = {5},
  year = {2016}
}
@article{Matamalas2016,
  abstract = {Understanding how people move within a geographical area, e.g. a city, a country or the whole world, is fundamental in several applications, from predicting the spatio-temporal evolution of an epidemic to inferring migration patterns. Mobile phone records provide an excellent proxy of human mobility, showing that movements exhibit a high level of memory. However, the precise role of memory in widely adopted proxies of mobility, as mobile phone records, is unknown. Here we use 560 million call detail records from Senegal to show that standard Markovian approaches, including higher order ones, fail in capturing real mobility patterns and introduce spurious movements never observed in reality. We introduce an adaptive memory-driven approach to overcome such issues. At variance with Markovian models, it is able to realistically model conditional waiting times, i.e. the probability to stay in a specific area depending on individuals' historical movements. Our results demonstrate that in standard mobility models the individuals tend to diffuse faster than observed in reality, whereas the predictions of the adaptive memory approach significantly agree with observations. We show that, as a consequence, the incidence and the geographical spread of a disease could be inadequately estimated when standard approaches are used, with crucial implications on resources deployment and policy-making during an epidemic outbreak.},
  archiveprefix = {arXiv},
  arxivid = {1603.05903},
  author = {Matamalas, Joan T. and {De Domenico}, Manlio and Arenas, Alex},
  doi = {10.1098/rsif.2016.0203},
  eprint = {1603.05903},
  isbn = {0000000309370},
  issn = {17425662},
  journal = {Journal of the Royal Society Interface},
  keywords = {Complex networks,Diffusion,Epidemic spreading,Human mobility,Markovian model},
  month = {aug},
  number = {121},
  pages = {20160203},
  pmid = {27581479},
  title = {{Assessing reliable human mobility patterns from higher order memory in mobile communications}},
  url = {http://rsif.royalsocietypublishing.org/lookup/doi/10.1098/rsif.2016.0203},
  volume = {13},
  year = {2016}
}
@incollection{Piwek2017,
  abstract = {In the following chapter, we review recent work on harnesses the sensors embedded in smartphones to understand individuals, and consider how such techniques might be used in behavior change interventions, and the ethical and practical issues such techniques might bring about.},
  author = {Piwek, L. and Joinson, Adam},
  booktitle = {Behavior Change Research and Theory: Psychological and Technological Perspectives},
  doi = {10.1016/B978-0-12-802690-8.00005-0},
  isbn = {9780128027059},
  issn = {0128027053},
  keywords = {Behavior,Emotions,Mood,Personality,Physical activity,Social interactions},
  pages = {137--165},
  publisher = {Elsevier},
  title = {{Automatic Tracking of Behavior With Smartphones: Potential for Behavior Change Interventions}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/B9780128026908000050},
  year = {2016}
}
@article{Jiang2016,
  abstract = {Well-established fine-scale urban mobility models today depend on detailed but cumbersome and expensive travel surveys for their calibration. Not much is known, however, about the set of mechanisms needed to generate complete mobility profiles if only using passive datasets with mostly sparse traces of individuals. In this study, we present a mechanistic modeling framework (TimeGeo) that effectively generates urban mobility patterns with resolution of 10 min and hundreds of meters. It ties together the inference of home and work activity locations from data, with the modeling of flexible activities (e.g., other) in space and time. The temporal choices are captured by only three features: the weekly home-based tour number, the dwell rate, and the burst rate. These combined generate for each individual: (i) stay duration of activities, (ii) number of visited locations per day, and (iii) daily mobility networks. These parameters capture how an individual deviates from the circadian rhythm of the population, and generate the wide spectrum of empirically observed mobility behaviors. The spatial choices of visited locations are modeled by a rank-based exploration and preferential return (r-EPR) mechanism that incorporates space in the EPR model. Finally, we show that a hierarchical multiplicative cascade method can measure the interaction between land use and generation of trips. In this way, urban structure is directly related to the observed distance of travels. This framework allows us to fully embrace the massive amount of individual data generated by information and communication technologies (ICTs) worldwide to comprehensively model urban mobility without travel surveys.},
  author = {Jiang, Shan and Yang, Yingxiang and Gupta, Siddharth and Veneziano, Daniele and Athavale, Shounak and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1073/pnas.1524261113},
  isbn = {1616240113},
  issn = {0027-8424},
  journal = {Proceedings of the National Academy of Sciences},
  month = {sep},
  number = {37},
  pages = {E5370--E5378},
  pmid = {27573826},
  title = {{The TimeGeo modeling framework for urban motility without travel surveys}},
  url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1524261113},
  volume = {113},
  year = {2016}
}
@article{Montjoye2016,
  abstract = {bandicoot is an open-source Python toolbox to extract more than 1442 features from stan- dard mobile phone metadata. bandicoot makes it easy for machine learning researchers and practitioners to load mobile phone data, to analyze and visualize them, and to extract robust features which can be used for various classification and clustering tasks. Emphasis is put on ease of use, consistency, and documentation. bandicoot has no dependencies and is distributed under MIT license},
  author = {de Montjoye, Yves-Alexandre and Rocher, Luc and Pentland, Alex Sandy},
  file = {::},
  isbn = {ISSN 1533-7928},
  issn = {15337928},
  journal = {Journal of Machine Learning Research},
  keywords = {cdr,feature engineering,mobile phone metadata,python,visualization},
  number = {175},
  pages = {1--5},
  title = {{bandicoot: a Python Toolbox for Mobile Phone Metadata}},
  url = {http://jmlr.org/papers/v17/15-593.html},
  volume = {17},
  year = {2016}
}
@article{Lu2017,
  abstract = {The advent of big data has aided understanding of the driving forces of human mobility, which is beneficial for many fields, such as mobility prediction, urban planning, and traffic management. However, the data sources used in many studies, such as mobile phone location and geo-tagged social media data, are sparsely sampled in the temporal scale. An individual's records can be distributed over a few hours a day, or a week, or over just a few hours a month. Thus, the representativeness of sparse mobile phone location data in characterizing human mobility requires analysis before using data to derive human mobility patterns. This paper investigates this important issue through an approach that uses subscriber mobile phone location data collected by a major carrier in Shenzhen, China. A dataset of over 5 million mobile phone subscribers that covers 24 h a day is used as a benchmark to test the representativeness of mobile phone location data on human mobility indicators, such as total travel distance, movement entropy, and radius of gyration. This study divides this dataset by hour, using 2- to 23-h segments to evaluate the representativeness due to the availability of mobile phone location data. The results show that different numbers of hourly segments affect estimations of human mobility indicators and can cause overestimations or underestimations from the individual perspective. On average, the total travel distance and movement entropy tend to be underestimated. The underestimation coefficient results for estimation of total travel distance are approximately linear, declining as the number of time segments increases, and the underestimation coefficient results for estimating movement entropy decline logarithmically as the time segments increase, whereas the radius of gyration tends to be more ambiguous due to the loss of isolated locations. This paper suggests that researchers should carefully interpret results derived from this type of sparse data in the era of big data.},
  author = {Lu, Shiwei and Fang, Zhixiang and Zhang, Xirui and Shaw, Shih-Lung and Yin, Ling and Zhao, Zhiyuan and Yang, Xiping and Lu, Shiwei and Fang, Zhixiang and Zhang, Xirui and Shaw, Shih-Lung and Yin, Ling and Zhao, Zhiyuan and Yang, Xiping},
  doi = {10.3390/ijgi6010007},
  issn = {2220-9964},
  journal = {ISPRS Int. J. of Geo-Information},
  keywords = {era of big data,human mobility,mobile phone location data,representative issue},
  number = {1},
  pages = {7},
  publisher = {Multidisciplinary Digital Publishing Institute},
  title = {{Understanding the Representativeness of Mobile Phone Location Data in Characterizing Human Mobility Indicators}},
  url = {http://www.mdpi.com/2220-9964/6/1/7},
  volume = {6},
  year = {2017}
}
@article{Munoz2016,
  abstract = {This paper explores how accountability might make otherwise obscure and inaccessible algorithms available for governance. The potential import and difficulty of accountability is made clear in the compelling narrative reproduced across recent popular and academic reports. Through this narrative we are told that algorithms trap us and control our lives, undermine our privacy, have power and an independent agential impact, at the same time as being inaccessible, reducing our opportunities for critical engagement. The paper suggests that STS sensibilities can provide a basis for scrutinizing the terms of the compelling narrative, disturbing the notion that algorithms have a single, essential characteristic and a predictable power or agency. In place of taking for granted the terms of the compelling narrative, ethnomethodological work on sense-making accounts is drawn together with more conventional approaches to accountability focused on openness and transparency. The paper uses empirical material from a study of the development of an "ethical," "smart" algorithmic videosurveillance system. The paper introduces the "ethical" algorithmic surveillance system, the approach to accountability developed, and some of the challenges of attempting algorithmic accountability in action. The paper concludes with reflections on future questions of algorithms and accountability.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1011.1669v3},
  author = {Neyland, Daniel},
  doi = {10.1177/0162243915598056},
  eprint = {arXiv:1011.1669v3},
  file = {::},
  isbn = {9788578110796},
  issn = {15528251},
  journal = {Science Technology and Human Values},
  keywords = {accountability,algorithms,ethics,governance,methodologies,surveillance},
  number = {1},
  pages = {50--76},
  pmid = {25246403},
  title = {{Bearing Account-able Witness to the Ethical Algorithmic System}},
  url = {https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/2016{\_}0504{\_}data{\_}discrimination.pdf https://www.whitehouse.gov/sites/default/files/microsites/ostp/2016{\_}0504{\_}data{\_}discrimination.pdf},
  volume = {41},
  year = {2016}
}
@article{Anagnostopoulos2016,
  abstract = {Cycling in smart cities can be safer if enhanced with a smart traffic lights infrastructure. A distributed smartphone-based sensing approach is a cost-effective infrastructure to enable cyclist-aware traffic lights system. In this article, we treat cyclist movement on a trajectory with a Boundary model able to reduce GPS sensor power consumption, while performing time-of-arrival estimation to the nearest light. A global quantitative metric of model efficiency is proposed for assessing the overall behavior of the model, and a false-positives rating qualitative metric is used to assess the recall of the model. We evaluated the model with confined yet realistic cycling experiments and verify the precision of our model using an Android application installed in participants' smartphones. We compared our model with previous literature, achieving a promising model for in-the-wild cycling scenarios.},
  author = {Anagnostopoulos, Theodoros and Ferreira, Denzil and Samodelkin, Alexander and Ahmed, Muzamil and Kostakos, Vassilis},
  doi = {10.1016/j.pmcj.2016.01.012},
  isbn = {15741192 (ISSN)},
  issn = {15741192},
  journal = {Pervasive and Mobile Computing},
  keywords = {Distributed model,Power consumption,Smartphone sensing,Time-of-arrival estimation},
  month = {sep},
  pages = {22--36},
  title = {{Cyclist-aware traffic lights through distributed smartphone sensing}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1574119216000249},
  volume = {31},
  year = {2016}
}
@article{Mamei2016,
  abstract = {We present a methodology to automatically identify users' relevant places from cellular network data.1In this work we used anonymized Call Detail Record (CDR) comprising information on where and when users access the cellular network. The key idea is to effectively cluster CDRs together and to weigh clusters to determine those associated to frequented places. The approach can identify users' home and work locations as well as other places (e.g., associated to leisure and night life). We evaluated our approach threefold: (i) on the basis of groundtruth information coming from a fraction of users whose relevant places were known, (ii) by comparing the resulting number of inhabitants of a given city with the number of inhabitants as extracted by the national census. (iii) Via stability analysis to verify the consistency of the extracted results across multiple time periods. Results show the effectiveness of our approach with an average 90{\%} precision and recall.},
  author = {Mamei, Marco and Colonna, Massimo and Galassi, Marco},
  doi = {10.1016/j.pmcj.2016.01.009},
  issn = {15741192},
  journal = {Pervasive and Mobile Computing},
  keywords = {CDR data,Mobility patterns,Place identification},
  month = {sep},
  pages = {147--158},
  title = {{Automatic identification of relevant places from cellular network data}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1574119216000213},
  volume = {31},
  year = {2016}
}
@article{Sundsoy2017,
  abstract = {Through seven publications this dissertation shows how anonymized mobile phone data can contribute to the social good and provide insights into human behaviour on a large scale. The size of the datasets analysed ranges from 500 million to 300 billion phone records, covering millions of people. The key contributions are two-fold:   1. Big Data for Social Good: Through prediction algorithms the results show how mobile phone data can be useful to predict important socio-economic indicators, such as income, illiteracy and poverty in developing countries. Such knowledge can be used to identify where vulnerable groups in society are, reduce economic shocks and is a critical component for monitoring poverty rates over time. Further, the dissertation demonstrates how mobile phone data can be used to better understand human behaviour during large shocks in society, exemplified by an analysis of data from the terror attack in Norway and a natural disaster on the south-coast in Bangladesh. This work leads to an increased understanding of how information spreads, and how millions of people move around. The intention is to identify displaced people faster, cheaper and more accurately than existing survey-based methods.   2. Big Data for efficient marketing: Finally, the dissertation offers an insight into how anonymised mobile phone data can be used to map out large social networks, covering millions of people, to understand how products spread inside these networks. Results show that by including social patterns and machine learning techniques in a large-scale marketing experiment in Asia, the adoption rate is increased by 13 times compared to the approach used by experienced marketers. A data-driven and scientific approach to marketing, through more tailored campaigns, contributes to less irrelevant offers for the customers, and better cost efficiency for the companies.},
  journal = {{arXiv}},
  archiveprefix = {arXiv},
  arxivid = {1702.08349},
  author = {Sunds{\o}y, P{\aa}l},
  eprint = {1702.08349},
  file = {::},
  month = {feb},
  pages = {166},
  title = {{Big Data for Social Sciences: Measuring patterns of human behavior through large-scale mobile phone data}},
  url = {http://arxiv.org/abs/1702.08349},
  year = {2017}
}
@article{Monsivais2017,
  abstract = {Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural entrainment with the sunlight. However, it is not completely understood to what extent this is the case. Here we exploit the large-scale data analysis techniques to study the mobile phone calling activity of people in large cities to infer the dynamics of urban daily rhythms. From the calling patterns of about 1,000,000 users spread over different cities but lying inside the same time-zone, we show that the onset and termination of the calling activity synchronizes with the east-west progression of the sun. We also find that the onset and termination of the calling activity of users follows a yearly dynamics, varying across seasons, and that its timings are entrained to solar midnight. Furthermore, we show that the average mid-sleep time of people living in urban areas depends on the age and gender of each cohort as a result of biological and social factors.},
  archiveprefix = {arXiv},
  arxivid = {1704.06187},
  author = {Monsivais, Daniel and Ghosh, Asim and Bhattacharya, Kunal and Dunbar, Robin I.M. and Kaski, Kimmo},
  doi = {10.1371/journal.pcbi.1005824},
  eprint = {1704.06187},
  file = {::},
  isbn = {1111111111},
  issn = {15537358},
  journal = {PLoS Computational Biology},
  month = {apr},
  number = {11},
  pmid = {29161270},
  title = {{Tracking urban human activity from mobile phone calling patterns}},
  url = {http://arxiv.org/abs/1704.06187 http://dx.doi.org/10.1371/journal.pcbi.1005824},
  volume = {13},
  year = {2017}
}
@article{Sarraute2017,
  abstract = {The large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobile phones allows us, not only to infer social networks between individuals, but also to observe the movements of these individuals in space and time. In this work, we investigate how these two related sources of information can be integrated within the context of detecting and analyzing large social events. We show that large social events can be characterized not only by an anomalous increase in activity of the antennas in the neighborhood of the event, but also by an increase in social relationships of the attendants present in the event. Moreover, having detected a large social event via increased antenna activity, we can use the network connections to infer whether an unobserved user was present at the event. More precisely, we address the following three challenges: (i) automatically detecting large social events via increased antenna activity; (ii) characterizing the social cohesion of the detected event; and (iii) analyzing the feasibility of inferring whether unobserved users were in the event.},
  journal = {{arXiv}},
  archiveprefix = {arXiv},
  arxivid = {1706.06253},
  author = {Sarraute, Carlos and Brea, Jorge and Burroni, Javier and Wehmuth, Klaus and Ziviani, Artur and Alvarez-Hamelin, J. I.},
  eprint = {1706.06253},
  file = {::},
  month = {jun},
  title = {{Social Events in a Time-Varying Mobile Phone Graph}},
  url = {http://arxiv.org/abs/1706.06253},
  year = {2017}
}
@article{Liao2017,
  abstract = {In this paper we investigate the behavioural differences between mobile phone customers with prepaid and postpaid subscriptions. Our study reveals that (a) postpaid customers are more active in terms of service usage and (b) there are strong structural correlations in the mobile phone call network as connections between cus-tomers of the same subscription type are much more frequent than those between customers of different subscription types. Based on these observations we provide methods to detect the subscription type of customers by using information about their personal call statistics, and also their egocentric networks simultaneously. The key of our first approach is to cast this classification problem as a problem of graph labelling, which can be solved by max-flow min-cut algorithms. Our experiments show that, by using both user attributes and relationships, the proposed graph la-belling approach is able to achieve a classification accuracy of ∼ 87{\%}, which out-performs by ∼ 7{\%} supervised learning methods using only user attributes. In our second problem we aim to infer the subscription type of customers of external op-erators. We propose via approximate methods to solve this problem by using node attributes, and a two-ways indirect inference method based on observed homophilic structural correlations. Our results have straightforward applications in behavioural prediction and personal marketing.},
  archiveprefix = {arXiv},
  arxivid = {arXiv:1706.10172v1},
  author = {Liao, Yongjun and Du, Wei and Karsai, M{\'{a}}rton and Sarraute, Carlos and Minnoni, Martin and Fleury, Eric},
  eprint = {arXiv:1706.10172v1},
  file = {::},
  month = {jun},
  title = {{Prepaid or Postpaid? That is the question. Novel Methods of Subscription Type Prediction in Mobile Phone Services}},
  url = {http://arxiv.org/abs/1706.10172},
  year = {2017}
}
@article{David-Barrett2017,
  abstract = {Earlier attempts to investigate the changes of the role of friendship in different life stages have failed due to lack of data. We close this gap by using a large data set of mobile phone calls from a European country in 2007, to study how the people's call patterns to their close social contacts are associated with age and gender of the callers. We hypothesize that (i) communication with peers, defined as callers of similar age, will be most important during the period of family formation and that (ii) the importance of best friends defined as same-sex callers of exactly the same age, will be stronger for women than for men. Results show that the frequency of phone calls with the same-sex peers in this population turns out to be relatively stable through life for both men and women. In line with the first hypothesis, there was a significant increase in the length of the phone calls for callers between ages 30 to 40 years. Partly in line with the second hypothesis, the increase in phone calls turned out to be particularly pronounced among females, although there were only minor gender differences in call frequencies. Furthermore, women tended to have long phone conversations with their same-age female friend, and also with somewhat older peers. In sum, we provide evidence from big data for the adult life stages at which peers are most important, and suggest that best friends appear to have a niche of their own in human sociality.},
  archiveprefix = {arXiv},
  arxivid = {1708.07759},
  author = {Society, Royal and Science, Open and Science, Computer},
  eprint = {1708.07759},
  file = {::},
  month = {aug},
  title = {{Peer relations with mobile phone data: Best friends and family formation}},
  url = {http://arxiv.org/abs/1708.07759},
  year = {2017}
}
@article{Sarker2017,
  abstract = {Mobile phone log data (e.g., phone call log) is not static as it is progressively added to day-by-day according to individ- ual's diverse behaviors with mobile phones. Since human behavior changes over time, the most recent pattern is more interesting and significant than older ones for predicting in- dividual's behavior. The goal of this poster paper is to iden- tify the recent behavioral data length dynamically from the entire phone log for recency-based behavior modeling. To the best of our knowledge, this is the first dynamic recent log-based study that takes into account individual's recent behavioral patterns for modeling their phone call behaviors.},
  archiveprefix = {arXiv},
  arxivid = {1711.06837},
  author = {Sarker, Iqbal H. and Kabir, Muhammad Ashad and Colman, Alan and Han, Jun},
  eprint = {1711.06837},
  file = {::},
  month = {nov},
  title = {{Identifying Recent Behavioral Data Length in Mobile Phone Log}},
  url = {http://arxiv.org/abs/1711.06837},
  year = {2017}
}
@article{Behadili2018,
  abstract = {The communication devices have produced digital traces for their users either voluntarily or not. This type of collective data can give powerful indications that are affecting the urban systems design and development. In this study mobile phone data during Armada event is investigated. Analyzing mobile phone traces gives conceptual views about individuals densities and their mobility patterns in the urban city. The geo-visualization and statistical techniques have been used for understanding human mobility collectively and individually. The undertaken substantial parameters are inter-event times, travel distances (displacements) and radius of gyration. They have been analyzed and simulated using computing platform by integrating various applications for huge database management, visualization, analysis, and simulation. Accordingly, the general population pattern law has been extracted. The study contribution outcomes have revealed both the individuals densities in static perspective and individuals mobility in dynamic perspective with multi levels of abstraction (macroscopic, mesoscopic, microscopic).},
  archiveprefix = {arXiv},
  arxivid = {1807.04865},
  author = {Behadili, Suhad Faisal and Bertelle, Cyrille and George, Loay E.},
  doi = {10.5815/ijitcs.2017.01.01},
  eprint = {1807.04865},
  file = {::},
  issn = {20749007},
  journal = {International Journal of Information Technology and Computer Science},
  month = {jul},
  number = {1},
  pages = {1--8},
  title = {{Adaptive Modeling of Urban Dynamics during Armada Event using CDRs}},
  url = {http://www.mecs-press.org/ijitcs/ijitcs-v9-n1/v9n1-1.html},
  volume = {9},
  year = {2017}
}
@article{Algizawy2017,
  author = {Algizawy, Essam and Ogawa, Tetsuji and El-Mahdy, Ahmed},
  doi = {10.1145/3046945},
  issn = {15564681},
  journal = {ACM Transactions on Knowledge Discovery from Data},
  keywords = {Mobile big data,adaptive HMM,cellular duration records,fine-grained spatial tracking,low cost},
  month = {jul},
  number = {4},
  pages = {1--38},
  publisher = {ACM},
  title = {{Real-Time Large-Scale Map Matching Using Mobile Phone Data}},
  url = {http://dl.acm.org/citation.cfm?doid=3119906.3046945},
  volume = {11},
  year = {2017}
}
@inproceedings{Sarker2017a,
  abstract = {Copyright {\textcopyright} 2017 ACM. Mobile phone log data is not static as it is progressively added to day-by-day according to individual's behavior. The goal of this position paper is to highlight the issues of traditional behavior modeling utilizing phone log data and to describe the key aspects that constitute the foundation of our recency-based behavior modeling for individual mobile phone users to overcome such issues.},
  address = {New York, New York, USA},
  author = {Sarker, I.H. and Kabir, M.A. and Colman, A. and Han, J.},
  booktitle = {UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers},
  doi = {10.1145/3123024.3124570},
  isbn = {9781450351904},
  keywords = {Incremental rule mining,Mobile data mining,Recency,User behavior modeling},
  pages = {916--921},
  publisher = {ACM Press},
  title = {{Understanding recency-based behavior model for individual Mobile phone users}},
  url = {http://dl.acm.org/citation.cfm?doid=3123024.3124570},
  year = {2017}
}
@article{Mehrotra2017,
  abstract = {User interaction patterns with mobile apps and notifications are generally complex due to the many factors involved. However a deep understanding of what influences them can lead to more acceptable applications that are able to deliver information at the right time. In this paper, we present for the first time an in-depth analysis of interaction behavior with notifications in relation to the location and activity of users. We conducted an in-situ study for a period of two weeks to collect more than 36,000 notifications, 17,000 instances of application usage, 77,000 location samples, and 487 days of daily activity entries from 26 students at a UK university. Our results show that users' attention towards new notifications and willingness to accept them are strongly linked to the location they are in and in minor part to their current activity. We consider both users' receptivity and attentiveness, and we show that different response behaviors are associated to different locations. These findings are fundamental from a design perspective since they allow us to understand how certain types of places are linked to specific types of interaction behavior. This information can be used as a basis for the development of novel intelligent mobile applications and services.},
  archiveprefix = {arXiv},
  arxivid = {1603.09436},
  author = {Mehrotra, Abhinav and M{\"{u}}ller, Sandrine R. and Harari, Gabriella M. and Gosling, Samuel D. and Mascolo, Cecilia and Musolesi, Mirco and Rentfrow, Peter J.},
  doi = {10.1145/3131901},
  eprint = {1603.09436},
  isbn = {9781450335492},
  issn = {24749567},
  journal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
  keywords = {Application Usage,Context-aware Computing,Mobile Sensing,Notifications},
  month = {sep},
  number = {3},
  pages = {1--22},
  pmid = {397311},
  publisher = {ACM},
  title = {{Understanding the Role of Places and Activities on Mobile Phone Interaction and Usage Patterns}},
  url = {http://dl.acm.org/citation.cfm?doid=3139486.3131901},
  volume = {1},
  year = {2017}
}
@article{Mehrotra2017a,
  author = {Mehrotra, Abhinav and Tsapeli, Fani and Hendley, Robert and Musolesi, Mirco},
  doi = {10.1145/3130948},
  issn = {24749567},
  journal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
  keywords = {Causality Analysis,Mobile Sensing},
  month = {sep},
  number = {3},
  pages = {1--21},
  publisher = {ACM},
  title = {{MyTraces}},
  url = {http://dl.acm.org/citation.cfm?doid=3139486.3130948},
  volume = {1},
  year = {2017}
}
@inproceedings{Hasan2017,
  address = {New York, New York, USA},
  author = {Hasan, Mahedi and Ali, Mohammed Eunus},
  booktitle = {Proceedings of the Ninth International Conference on Information and Communication Technologies and Development  - ICTD '17},
  doi = {10.1145/3136560.3136566},
  isbn = {9781450352772},
  keywords = {call detail records,mobile users,traffic jam,travel time estimation},
  pages = {1--11},
  publisher = {ACM Press},
  title = {{Estimating Travel Time of Dhaka City from Mobile Phone Call Detail Records}},
  url = {http://dl.acm.org/citation.cfm?doid=3136560.3136566},
  year = {2017}
}
@article{Ahmed2017,
  abstract = {Prior research on technology use in the Global South suggests that people in marginalized communities frequently share a single device among multiple individuals. However, the data privacy challenges and tensions that arise when people share devices have not been studied in depth. This paper presents a qualitative study with 72 participants that analyzes how families in Bangladesh currently share mobile phones, their usage patterns, and the tensions and challenges that arise as individuals seek to protect the privacy of their personal data. We show how people share devices out of economic need, but also because sharing is a social and cultural practice that is deeply embedded in Bangladeshi society. We also discuss how prevalent power relationships affect sharing practices and reveal gender dynamics that impact the privacy of women's data. Finally, we highlight strategies that participants adopted to protect their private data from the people with whom they share devices. Taken together, our findings have broad implications that advance the CSCW community's understanding of digital privacy outside the Western world.},
  author = {Ahmed, Syed Ishtiaque and Haque, Md. Romael and Chen, Jay and Dell, Nicola},
  doi = {10.1145/3134652},
  issn = {25730142},
  journal = {Proceedings of the ACM on Human-Computer Interaction},
  keywords = {access,hci4d,ictd,mobile devices,privacy,shared use},
  pages = {1--20},
  publisher = {ACM},
  title = {{Digital Privacy Challenges with Shared Mobile Phone Use in Bangladesh}},
  url = {https://dl.acm.org/citation.cfm?id=3171581.3134652{\%}0Ahttp://dl.acm.org/citation.cfm?doid=3171581.3134652},
  volume = {1},
  year = {2017}
}
@article{Huang2017,
  author = {Huang, Wei and Fan, Hongchao and Zipf, Alexander},
  doi = {10.3390/ijgi6100305},
  issn = {2220-9964},
  journal = {ISPRS International Journal of Geo-Information},
  month = {oct},
  number = {10},
  pages = {305},
  title = {{Towards Detecting the Crowd Involved in Social Events}},
  url = {http://www.mdpi.com/2220-9964/6/10/305},
  volume = {6},
  year = {2017}
}
@article{Kashiyama2017,
  abstract = {Understanding people flow at a citywide level is critical for urban planning and commercial development. Thanks to the ubiquity of human location tracking devices, many studies on people mass movement with mobility logs have been conducted. However, high cost and severe privacy policy constraints still complicate utilization of these data in practice. There is no dataset that anyone can freely access, use, modify, and share for any purpose. To tackle this problem, we propose a novel dataset creation approach (called Open PFLOW) that continuously reports the spatiotemporal positions of all individual's in urban areas based on open data. With fully consideration of the privacy protection, each entity in our dataset does not match the actual movement of any real person, so that the dataset can be totally open to public as part of data infrastructure. Because the result is shown at a disaggregate level, users can freely modify, process, and visualize the dataset for any purpose. We evaluate the accuracy of the dataset by comparing it with commercial datasets and traffic census indicates that it has a high correlation with mesh population and link-based traffic volume.},
  author = {Kashiyama, Takehiro and Pang, Yanbo and Sekimoto, Yoshihide},
  doi = {10.1016/j.trc.2017.09.016},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {Attitude formation,Data visualization,Open data,Public Participation GIS (PPGIS),Urban simulation},
  month = {dec},
  pages = {249--267},
  title = {{Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0968090X17302644},
  volume = {85},
  year = {2017}
}
@article{Jiang2017,
  abstract = {In this study, with Singapore as an example, we demonstrate how we can use mobile phone call detail record (CDR) data, which contains millions of anonymous users, to extract individual mobility networks comparable to the activity-based approach. Such an approach is widely used in the transportation planning practice to develop urban micro simulations of individual daily activities and travel; yet it depends highly on detailed travel survey data to capture individual activity-based behavior. We provide an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes. With growing ubiquitous mobile sensing, and shrinking labor and fiscal resources in the public sector globally, the method presented in this research can be used as a low-cost alternative for transportation and planning agencies to understand the human activity patterns in cities, and provide targeted plans for future sustainable development.},
  author = {Jiang, Shan and Ferreira, Joseph and Gonzalez, Marta C.},
  doi = {10.1109/TBDATA.2016.2631141},
  issn = {2332-7790},
  journal = {IEEE Transactions on Big Data},
  month = {jun},
  number = {2},
  pages = {208--219},
  title = {{Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore}},
  url = {http://ieeexplore.ieee.org/document/7755745/},
  volume = {3},
  year = {2017}
}
@book{IEEEStaff2016,
  abstract = {Scholarly {\&} Professional This conference provides an opportunity for prominent international specialists, researchers, and engineers to present and observe the latest research, results, and ideas in the area of Computer and Communications The objective of ICCC 2016 is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting edge development in the field.},
  author = {Section, First},
  isbn = {9781467390279},
  publisher = {IEEE},
  title = {{2017 3rd IEEE International Conference on Computer and Communications}},
  year = {2017}
}
@inproceedings{FengLing2016,
  abstract = {{\textcopyright} 2016 IEEE. As the mobile devices are used widely, it is possible to research human mobility and behaviors by using the increasing mobile phone data. This paper aims to mine travel behaviors of users in Hainan, a popular tourist destination in China. The data is Call Detail Records (CDR) and Point of Interest (POI) information. Specifically, a data processing platform is developed. It can convert the large scale of CDR and location-based data to trajectories by utilizing the cross-domain data. Furthermore, a hierarchical analytical method is built on our platform to identify the difference of tourists respectively in temporal and spatial dimensions. Finally, the most popular travel patterns and top 3 travel routes for short-term tourists in Sanya are discovered from the trajectories of tourists according to the platform.},
  author = {Ling, Feng and Sun, Tianyue and Zhu, Xinning and Chen, Qingqing and Tang, Xiaosheng and Ke, Xin},
  booktitle = {2016 2nd IEEE International Conference on Computer and Communications, ICCC 2016 - Proceedings},
  doi = {10.1109/CompComm.2016.7924957},
  isbn = {9781467390262},
  keywords = {Hierarchical analytical method,Mobile phone data,Platform,Travel behavior},
  month = {oct},
  pages = {1524--1529},
  publisher = {IEEE},
  title = {{Mining travel behaviors of tourists with mobile phone data: A case study in Hainan}},
  url = {http://ieeexplore.ieee.org/document/7924957/},
  year = {2017}
}
@article{Iglesias2017,
  abstract = {In the competitive telecommunications market, the information that the mobile telecom operators can obtain by regularly analysing their massive stored call logs, is of great interest. Although the data that can be extracted nowadays from mobile phones have been enriched with much information, the data solely from the call logs can give us vital information about the customers. This information is usually related with the calling behaviour of their customers and it can be used to manage them. However, the analysis of these data is normally very complex because of the vast data stream to analyse. Thus, efficient data mining techniques need to be used for this purpose. In this paper, a novel approach to analyse call detail records (CDR) is proposed, with the main goal to extract and cluster different calling patterns or behaviours, and to detect outliers. The main novelty of this approach is that it works in real-time using an evolving and recursive framework.},
  author = {Iglesias, Jos{\'{e}} and Ledezma, Agapito and Sanchis, Araceli and Angelov, Plamen},
  doi = {10.3390/app7080798},
  issn = {2076-3417},
  journal = {Applied Sciences},
  month = {aug},
  number = {8},
  pages = {798},
  title = {{Real-Time Recognition of Calling Pattern and Behaviour of Mobile Phone Users through Anomaly Detection and Dynamically-Evolving Clustering}},
  url = {http://www.mdpi.com/2076-3417/7/8/798},
  volume = {7},
  year = {2017}
}
@article{Ricciato2017,
  abstract = {We address the problem of estimating the population density from mobile phone data. After critically examining the relevant network-based data sources (CDR, VLR and passive monitoring systems) a novel methodology is presented with two key novelties. First, it enables the fusion of cell-level and Location Area-level data from heterogeneous data sources. Second, it considers a novel tessellation scheme based on cell coverage maps, instead of cell tower locations. Furthermore, it allows to integrate data from different network operators onto a common reference grid. Within the proposed framework, a Maximum-Likelihood formulation for the population density estimation problem is developed and tested via simulations, showing a significant gain over existing Voronoi-based schemes.},
  author = {Ricciato, Fabio and Widhalm, Peter and Pantisano, Francesco and Craglia, Massimo},
  doi = {10.1016/j.pmcj.2016.04.009},
  issn = {15741192},
  journal = {Pervasive and Mobile Computing},
  keywords = {Augmenting official statistics,Interoperability,Mobile network data},
  month = {feb},
  pages = {65--82},
  title = {{Beyond the “single-operator, CDR-only” paradigm: An interoperable framework for mobile phone network data analyses and population density estimation}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S1574119216300323},
  volume = {35},
  year = {2017}
}
@article{Gordon2017,
  abstract = {This study explores the relationship between mobile phones and users' identities in three cultures that differ geographically, historically, and culturally: Oman, an Islamic social monarchy in the Arabian Gulf; Ukraine, a post-Soviet Eastern European country; and the United States of America. A Likert-style questionnaire that also included open-ended questions was distributed to 393 college students to elicit answers on how they relate to their mobile phones. Findings indicate that mobile phone users of different nationalities and genders perceive and use their mobile phones differently for self-expression and identity display, with Omani women most likely to orient to their phones as identity-relevant, and Ukrainian men least likely to do so. Americans showed more mixed results, with American women more prone to treat their mobile phones as objects that relate to identity expression. Further, while Ukrainians and Americans tended to view their mobile phones primarily through the lens of utility, Omanis tended to take a more affective/romantic perspective. To explain these findings, we demonstrate, following Al Zidjaly and Gordon (2012), that mobile phones are productively understood as what Scollon (2001) calls cultural tools, or the material and symbolic means people use in culturally- and historically-enabled and -constrained ways to accomplish actions such as identity display.},
  author = {Gordon, Cynthia and {Al Zidjaly}, Najma and Tovares, Alla V.},
  doi = {10.1016/j.dcm.2017.01.006},
  issn = {22116958},
  journal = {Discourse, Context and Media},
  keywords = {Cultural practices,Cultural tools,Gendered practices,Identity,Mobile phones},
  month = {jun},
  pages = {9--19},
  title = {{Mobile phones as cultural tools for identity construction among college students in Oman, Ukraine, and the U.S.}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S2211695816300812},
  volume = {17},
  year = {2017}
}
@article{Hofman2017,
  abstract = {Historically, social scientists have sought out explanations of human and social phenomena that provide interpretable causal mechanisms, while often ignoring their predictive accuracy. We argue that the increasingly computational nature of social science is beginning to reverse this traditional bias against prediction; however, it has also highlighted three important issues that require resolution. First, current practices for evaluating predictions must be better standardized. Second, theoretical limits to predictive accuracy in complex social systems must be better characterized, thereby setting expectations for what can be predicted or explained. Third, predictive accuracy and interpretability must be recognized as complements, not substitutes, when evaluating explanations. Resolving these three issues will lead to better, more replicable, and more useful social science.},
  author = {Hofman, Jake M. and Sharma, Amit and Watts, Duncan J.},
  journal = {Science},
  doi = {10.1126/science.aal3856},
  isbn = {0036-8075},
  issn = {10959203},
  number = {6324},
  pages = {486--488},
  pmid = {28154051},
  title = {{Prediction and explanation in social systems}},
  url = {http://science.sciencemag.org/},
  volume = {355},
  year = {2017}
}
@article{Dong2017,
  abstract = {The understanding and modeling of human purchase behavior in city environment can have important implications in the study of urban economy and in the design and organization of cities. In this article, we study human purchase behavior at the community level and argue that people who live in different communities but work at close-by locations could act as "social bridges" between the respective communities and that they are correlated with similarity in community purchase behavior. We provide empirical evidence by studying millions of credit card transaction records for tens of thousands of individuals in a city environment during a period of three months. More specifically, we show that the number of social bridges between communities is a much stronger indicator of similarity in their purchase behavior than traditionally considered factors such as income and sociodemographic variables. Our findings also suggest that such an effect varies across different merchant categories, that the presence of female customers in social bridges is a stronger indicator compared to that o f their male counterparts, and that there seems to be a geographical constraint for this effect, all of which may have implications in the studies of urban economy and data-driven urban planning.},
  author = {Dong, Xiaowen and Suhara, Yoshihiko and Bozkaya, Bur{\c{c}}in and Singh, Vivek K. and Lepri, Bruno and Pentland, Alex ‘Sandy'},
  doi = {10.1145/3149409},
  issn = {21576904},
  journal = {ACM Transactions on Intelligent Systems and Technology},
  month = {dec},
  number = {3},
  pages = {1--29},
  title = {{Social Bridges in Urban Purchase Behavior}},
  url = {http://dl.acm.org/citation.cfm?doid=3167125.3149409},
  volume = {9},
  year = {2017}
}
@article{DiClemente2018,
  abstract = {Zipf-like distributions characterize a wide set of phenomena in physics, biology, economics and social sciences. In human activities, Zipf-laws describe for example the frequency of words appearance in a text or the purchases types in shopping patterns. In the latter, the uneven distribution of transaction types is bound with the temporal sequences of purchases of individual choices. In this work, we define a new framework using a text compression technique on the sequences of credit card purchases to detect ubiquitous patterns of collective behavior. Clustering the consumers by their similarity in purchases sequences, we detect five consumer groups. Remarkably, post checking, individuals in each group are also similar in their age, total expenditure, gender, and the diversity of their social and mobility networks extracted by their mobile phone records. By properly deconstructing transaction data with Zipf-like distributions, this method uncovers sets of significant sequences that reveal insights on collective human behavior.},
  archiveprefix = {arXiv},
  arxivid = {1703.00409},
  author = {{Di Clemente}, Riccardo and Luengo-Oroz, Miguel and Travizano, Matias and Xu, Sharon and Vaitla, Bapu and Gonz{\'{a}}lez, Marta C.},
  doi = {10.1038/s41467-018-05690-8},
  eprint = {1703.00409},
  file = {::},
  isbn = {4146701805},
  issn = {2041-1723},
  journal = {Nature Comm.},
  keywords = {Complex networks,Interdisciplinary studies,Society},
  number = {1},
  pages = {3330},
  publisher = {Nature Publishing Group},
  title = {{Sequence of purchases in credit card data reveal life styles in urban populations}},
  url = {http://arxiv.org/abs/1703.00409},
  volume = {9},
  year = {2017}
}
@misc{Zacharek2017,
  abstract = {Amazing quote from a hotel housekeeper: "It's crazy that people think that if they pay for the room, they are paying for sexual service." About 2/3 of the way down, behind one of the photos.},
  author = {Zacharek, Stephanie and Dockterman, Elian and Edwards, Haley Sweetland},
  booktitle = {Time},
  title = {{TIME Person of the Year 2017: The Silence Breakers}},
  url = {http://time.com/time-person-of-the-year-2017-silence-breakers/},
  urldate = {2018-08-21},
  year = {2017}
}
@inproceedings{Messias2017,
  abstract = {Social media is considered a democratic space in which people connect and interact with each other regardless of their gender, race, or any other demographic factor. Despite numerous efforts that explore demographic factors in social media, it is still unclear whether social media perpetuates old inequalities from the offline world. In this paper, we attempt to identify gender and race of Twitter users located in U.S. using advanced image processing algorithms from Face++. Then, we investigate how different demographic groups (i.e. male/female, Asian/Black/White) connect with other. We quantify to what extent one group follow and interact with each other and the extent to which these connections and interactions reflect in inequalities in Twitter. Our analysis shows that users identified as White and male tend to attain higher positions in Twitter, in terms of the number of followers and number of times in user's lists. We hope our effort can stimulate the development of new theories of demographic information in the online space.},
  address = {New York, New York, USA},
  archiveprefix = {arXiv},
  arxivid = {1706.08619},
  author = {Messias, Johnnatan and Vikatos, Pantelis and Benevenuto, Fabricio},
  booktitle = {Proceedings of the International Conference on Web Intelligence  - WI '17},
  doi = {10.1145/3106426.3106472},
  eprint = {1706.08619},
  isbn = {9781450349512},
  pages = {266--274},
  publisher = {ACM Press},
  title = {{White, Man, and Highly Followed: Gender and Race Inequalities in Twitter}},
  url = {http://arxiv.org/abs/1706.08619{\%}0Ahttp://dx.doi.org/10.1145/3106426.3106472},
  year = {2017}
}
@article{Graells-Garrido2017,
  abstract = {Pok{\'{e}}mon Go, a location-based game that uses augmented reality techniques, received unprecedented media coverage due to claims that it allowed for greater access to public spaces, increasing the number of people out on the streets, and generally improving health, social, and security indices. However, the true impact of Pok{\'{e}}mon Go on people's mobility patterns in a city is still largely unknown. In this paper, we perform a natural experiment using data from mobile phone networks to evaluate the effect of Pok{\'{e}}mon Go on the pulse of a big city: Santiago, capital of Chile. We found significant effects of the game on the floating population of Santiago compared to movement prior to the game's release in August 2016: in the following week, up to 13.8{\%} more people spent time outside at certain times of the day, even if they do not seem to go out of their usual way. These effects were found by performing regressions using count models over the states of the cellphone network during each day under study. The models used controlled for land use, daily patterns, and points of interest in the city. Our results indicate that, on business days, there are more people on the street at commuting times, meaning that people did not change their daily routines but slightly adapted them to play the game. Conversely, on Saturday and Sunday night, people indeed went out to play, but favored places close to where they live. Even if the statistical effects of the game do not reflect the massive change in mobility behavior portrayed by the media, at least in terms of expanse, they do show how ‘the street' may become a new place of leisure. This change should have an impact on long-term infrastructure investment by city officials, and on the drafting of public policies aimed at stimulating pedestrian traffic.},
  archiveprefix = {arXiv},
  arxivid = {1610.08098},
  author = {Graells-Garrido, Eduardo and Ferres, Leo and Caro, Diego and Bravo, Loreto},
  doi = {10.1140/epjds/s13688-017-0119-3},
  eprint = {1610.08098},
  file = {::},
  isbn = {2193-1127},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {Pok{\'{e}}mon,call detail records,floating population,mobile phone data,urban informatics},
  month = {dec},
  number = {1},
  pages = {23},
  publisher = {Springer Berlin Heidelberg},
  title = {{The effect of Pok{\'{e}}mon Go on the pulse of the city: a natural experiment}},
  url = {http://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-017-0119-3},
  volume = {6},
  year = {2017}
}
@article{Cao2017,
  abstract = {The 21st century has ushered in the age of big data and data economy, in which data DNA, which carries im-portant knowledge, insights, and potential, has become an intrinsic constituent of all data-based organisms. An appropriate understanding of data DNA and its organisms relies on the new field of data science and its keystone, analytics. Although it is widely debated whether big data is only hype and buzz, and data science is still in a very early phase, significant challenges and opportunities are emerging or have been inspired by the research, innovation, business, profession, and education of data science. This article provides a com-prehensive survey and tutorial of the fundamental aspects of data science: the evolution from data analysis to data science, the data science concepts, a big picture of the era of data science, the major challenges and directions in data innovation, the nature of data analytics, new industrialization and service opportunities in the data economy, the profession and competency of data education, and the future of data science. This article is the first in the field to draw a comprehensive big picture, in addition to offering rich observations, lessons, and thinking about data science and analytics.},
  author = {Cao, Longbing},
  doi = {10.1145/3076253},
  file = {::},
  isbn = {978-1-4842-2252-2},
  issn = {03600300},
  journal = {ACM Computing Surveys},
  keywords = {Big data,advanced analytics,big data analytics,computing,data DNA,data analysis,data analytics,data economy,data education,data engineering,data industry,data innovation,data profession,data science,data scientist,data service,informatics,statistics},
  month = {jun},
  number = {3},
  pages = {1--42},
  publisher = {ACM},
  title = {{Data Science}},
  url = {http://dl.acm.org/citation.cfm?doid=3101309.3076253},
  volume = {50},
  year = {2017}
}
@article{Tosi2017,
  abstract = {Efficient mobility is a key aspect for the future smart cities. The real added value for smart cities is the real-time optimization of vehicular and public transportation flows to reduce traffic congestions, costs, and emissions. Observing constantly the behaviour of people moving around the city can help policy makers to act promptly and to fix congested flows dynamically. In this paper, we describe from a technical point-of-view an original use of big data (coming from the cellular network of the Vodafone Italy Telco operator) to compute mobility patterns for smart cities. The paper also discusses five innovative mobility patterns that describe different mobility scenarios of the city, starting from how people move around point-of-interests of the city in real time. The mobility patterns have been experimentally validated in a real industrial setting and for the Milan metropolitan city. The study conducted confirmed the quality of the patterns and their importance in smart cities, by showing how cell phone big data can complete other sources of people information. These mobility patterns can be exploited by policy makers to improve the mobility in a city, or by Navigation Systems and Journey Planners to provide final users with accurate travel plans.},
  author = {Tosi, Davide},
  doi = {10.1007/s41060-017-0061-2},
  issn = {2364-415X},
  journal = {International Journal of Data Science and Analytics},
  month = {dec},
  number = {4},
  pages = {265--284},
  title = {{Cell phone big data to compute mobility scenarios for future smart cities}},
  url = {http://link.springer.com/10.1007/s41060-017-0061-2},
  volume = {4},
  year = {2017}
}
@incollection{Horn2017,
  abstract = {Now more than ever, the design of systems and devices for effective and safe healthcare delivery has taken center stage. And the importance of human factors and ergonomics in achieving this goal can't be ignored. Underlining the utility of research in achieving effective design, Advances in Human Aspects of Healthcare discusses how human factors and ergonomics principles can be applied to improve quality, safety, efficiency, and effectiveness in patient care. Topics include the design of work environments to improve satisfaction and well-being of patients, healthcare providers, and professionals. The book explores new approaches for improving healthcare devices such as portable ultrasound systems, better work design, and effective communications and systems support. It also examines healthcare informatics for the public and usability for patient users, building on results from usability studies for medical personnel. Several chapters explore quality and safety while others examine medical error for risk factors and information transfer in error reduction. The book provides an integrated review of physical, cognitive, and organizational aspects that facilitates a systems approach to implementation. These features and more allow practitioners to gain a deeper understanding of the issues in healthcare delivery and the role ergonomics and human factors can play in solving them.},
  author = {Horn, Christopher and Gursch, Heimo and Kern, Roman and Cik, Michael},
  booktitle = {Advances in Intelligent Systems and Computing},
  doi = {10.1007/978-3-319-41682-3_68},
  isbn = {9783319416816},
  issn = {21945357},
  keywords = {Big data,Floating phone data (FPD),Hadoop,Origin-destination (OD) matrices,Transportation planning,Travel demand},
  pages = {823--833},
  title = {{QZtool—Automatically generated origin-destination matrices from cell phone trajectories}},
  url = {http://link.springer.com/10.1007/978-3-319-41682-3{\_}68},
  volume = {484},
  year = {2017},
  publisher = {Springer}
}
@misc{Thomson2018,
  author = {Thomson, Eduardo},
  booktitle = {Bloomberg},
  title = {{Chile's Mobile War Heats Up as Incumbents Strike Back at Newer Rivals - Bloomberg}},
  url = {https://www.bloomberg.com/news/articles/2018-04-06/newcomer-cries-foul-as-entel-counterattacks-in-chile-mobile-war},
  urldate = {2018-08-15},
  year = {2018}
}
@incollection{Chi2011,
  abstract = {Earthquake is a fatal disaster in the world, and it is expected to occur in Taiwan with high probability. The Central Weather Bureau of Taiwan develops the early earthquake warning system as other countries. In this paper, we introduce the current development status for the earthquake early warning system. To integrate the various smart devices, we adopt SIP page-mode as the next generation earthquake early warning alert protocol. Due to the lack of multicast support in the general IP network, we try to deliver the warning message to multiple receivers in time base on SIP architecture, location information, priority with IoT devices and in time control-theoretic algorithm. With the proposed algorithm, we can not only reduce the burst message traffic for network but also send the message in time. {\textcopyright} 2011 Springer-Verlag.},
  author = {Chi, Ting Yun and Chen, Chun Hao and Chao, Han Chieh and Kuo, Sy Yen},
  booktitle = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-642-23641-9_15},
  isbn = {9783642236402},
  issn = {03029743},
  keywords = {Earthquake,IM/SIP,control-theoretic,emergency message,location information},
  pages = {161--173},
  title = {{An efficient earthquake early warning message delivery algorithm using an in time control-theoretic approach}},
  url = {http://link.springer.com/10.1007/978-3-642-23641-9{\_}15},
  volume = {6905 LNCS},
  publisher = {Springer--Verlag},
  year = {2011}
}
@article{Rubrichi2017,
  abstract = {Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment and mitigation processes during epidemics. Using a real-world dataset from Ivory Coast, this work presents an attempt to unveil the socio-geographical heterogeneity of disease transmission dynamics. By employing a spatially explicit meta-population epidemic model derived from mobile phone Call Detail Records (CDRs), we investigate how the differences in mobility patterns may affect the course of a hypothetical infectious disease outbreak. We consider different existing measures of the spatial dimension of human mobility and interactions, and we analyse their relevance in identifying the highest risk sub-population of individuals, as the best candidates for isolation countermeasures. The approaches presented in this paper provide further evidence that mobile phone data can be effectively exploited to facilitate our understanding of individuals' spatial behaviour and its relationship with the risk of infectious diseases' contagion. In particular, we show that CDRs-based indicators of individuals' spatial activities and interactions hold promise for gaining insight of contagion heterogeneity and thus for developing mitigation strategies to support decision-making during country-level epidemics.},
  archiveprefix = {arXiv},
  arxivid = {1706.00690},
  author = {Rubrichi, Stefania and Smoreda, Zbigniew and Musolesi, Mirco},
  doi = {10.1140/epjds/s13688-018-0145-9},
  eprint = {1706.00690},
  file = {::},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {Epidemic spread,Human mobility,Mobile phone data,Spatial networks},
  month = {jun},
  number = {1},
  title = {{A comparison of spatial-based targeted disease mitigation strategies using mobile phone data}},
  url = {http://arxiv.org/abs/1706.00690},
  volume = {7},
  year = {2018}
}
@article{Bassolas2018,
  abstract = {Activity-based models appeared as an answer to the limitations of the traditional trip-based and tour-based four-stage models. The fundamental assumption of activity-based models is that travel demand is originated from people performing their daily activities. This is why they include a consistent representation of time, of the persons and households, time-dependent routing, and microsimulation of travel demand and traffic. In spite of their potential to simulate traffic demand management policies, their practical application is still limited. One of the main reasons is that these models require a huge amount of very detailed input data hard to get with surveys. However, the pervasive use of mobile devices has brought a valuable new source of data. The work presented here has a twofold objective: first, to demonstrate the capability of mobile phone records to feed activity-based transport models, and, second, to assert the advantages of using activity-based models to estimate the effects of traffic demand management policies. Activity diaries for the metropolitan area of Barcelona are reconstructed from mobile phone records. This information is then employed as input for building a transport MATSim model of the city. The model calibration and validation process proves the quality of the activity diaries obtained. The possible impacts of a cordon toll policy applied to two different areas of the city and at different times of the day is then studied. Our results show the way in which the modal share is modified in each of the considered scenario. The possibility of evaluating the effects of the policy at both aggregated and traveller level, together with the ability of the model to capture policy impacts beyond the cordon toll area confirm the advantages of activity-based models for the evaluation of traffic demand management policies.},
  archiveprefix = {arXiv},
  arxivid = {1803.06375},
  author = {Bassolas, Aleix and Ramasco, Jose J. and Herranz, Ricardo and Cantu-Ros, Oliva G.},
  eprint = {1803.06375},
  file = {::},
  month = {mar},
  title = {{Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona}},
  url = {http://arxiv.org/abs/1803.06375},
  year = {2018}
}
@techreport{Jacques2018,
  abstract = {Mobile phones are now widely adopted by most of the world population. Each time a call is made (or an SMS sent), a Call Detail Record (CDR) is generated by the telecom companies for billing purpose. These metadata provide information on when, how, from where and with whom we communicate. Conceptually, they can be described as a geospatial, dynamic, weighted and directed network. Applications of CDRs for development are numerous. They have been used to model the spread of infectious diseases, study road traffic, support electrification planning strategies or map socio-economic level of population. While massive, CDRs are not statistically representative of the whole population due to several sources of bias (market, usage, spatial and temporal resolution). Furthermore, mobile phone metadata are held by telecom companies. Consequently, their access is not necessarily straightforward and can seriously hamper any operational application. Finally, a trade-off exists between privacy and utility when using sensitive data like CDRs. New initiatives such as Open Algorithm might help to deal with these fundamental questions by allowing researchers to run algorithms on the data that remain safely stored behind the firewall of the providers.},
  institution = {{arXiv}},
  archiveprefix = {arXiv},
  number = {1806.03086},
  author = {Jacques, Damien C.},
  eprint = {1806.03086},
  title = {{Mobile Phone Metadata for Development}},
  url = {http://arxiv.org/abs/1806.03086},
  year = {2018}
}
@article{Noriega-Campero2018,
  abstract = {Today's age of data holds high potential to enhance the way we pursue and monitor progress in the fields of development and humanitarian action. We study the relation between data utility and privacy risk in large-scale behavioral data, focusing on mobile phone metadata as paradigmatic domain. To measure utility, we survey experts about the value of mobile phone metadata at various spatial and temporal granularity levels. To measure privacy, we propose a formal and intuitive measure of reidentification risk{\$}\backslashunicode{\{}x2014{\}}{\$}the information ratio{\$}\backslashunicode{\{}x2014{\}}{\$}and compute it at each granularity level. Our results confirm the existence of a stark tradeoff between data utility and reidentifiability, where the most valuable datasets are also most prone to reidentification. When data is specified at ZIP-code and hourly levels, outside knowledge of only 7{\%} of a person's data suffices for reidentification and retrieval of the remaining 93{\%}. In contrast, in the least valuable dataset, specified at municipality and daily levels, reidentification requires on average outside knowledge of 51{\%}, or 31 data points, of a person's data to retrieve the remaining 49{\%}. Overall, our findings show that coarsening data directly erodes its value, and highlight the need for using data-coarsening, not as stand-alone mechanism, but in combination with data-sharing models that provide adjustable degrees of accountability and security.},
  archiveprefix = {arXiv},
  arxivid = {1808.00160},
  author = {Noriega-campero, Alejandro and Montjoye, Yves A De and Pentland, Alex},
  eprint = {1808.00160},
  file = {::},
  keywords = {data,data for development,data privacy,mobile phone,mobility data,privacy-utility tradeoff,reidentification},
  month = {aug},
  pages = {1--9},
  title = {{Mapping the Privacy-Utility Tradeoff in Mobile Phone Data for Development}},
  url = {http://arxiv.org/abs/1808.00160},
  year = {2018}
}
@inproceedings{Weld2018,
  address = {New York, New York, USA},
  author = {Weld, Galen and Perrier, Trevor and Aker, Jenny and Blumenstock, Joshua E. and Dillon, Brian and Kamanzi, Adalbertus and Kokushubira, Editha and Webster, Jennifer and Anderson, Richard J.},
  booktitle = {Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems  - CHI '18},
  doi = {10.1145/3173574.3173707},
  isbn = {9781450356206},
  keywords = {basic mobile phones,hci4d,ict4d,tanzania,ussd},
  pages = {1--12},
  publisher = {ACM Press},
  title = {{eKichabi}},
  url = {http://dl.acm.org/citation.cfm?doid=3173574.3173707},
  year = {2018}
}
@inproceedings{Bati2018,
  address = {New York, New York, USA},
  author = {Bati, Ghassan F. and Singh, Vivek K.},
  booktitle = {Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems  - CHI '18},
  doi = {10.1145/3173574.3173904},
  isbn = {9781450356206},
  keywords = {behavioral sensing,mobile sensing,trust propensity},
  pages = {1--14},
  publisher = {ACM Press},
  title = {{Trust Us}},
  url = {http://dl.acm.org/citation.cfm?doid=3173574.3173904},
  year = {2018}
}
@article{Qin2018,
  author = {Qin, Tian and Shangguan, Wufan and Song, Guojie and Tang, J I E},
  doi = {10.1145/3201577},
  issn = {15564681},
  journal = {ACM Transactions on Knowledge Discovery from Data},
  keywords = {Routine mining,mobile phone data,spatio-temporal pattern},
  month = {jun},
  number = {5},
  pages = {1--24},
  publisher = {ACM},
  title = {{Spatio-Temporal Routine Mining on Mobile Phone Data}},
  url = {http://dl.acm.org/citation.cfm?doid=3234931.3201577},
  volume = {12},
  year = {2018}
}
@article{Wang2009,
  abstract = {We modeled the mobility of mobile phone users in order to study the fundamental spreading patterns that characterize a mobile virus outbreak. We find that although Bluetooth viruses can reach all susceptible handsets with time, they spread slowly because of human mobility, offering ample opportunities to deploy antiviral software. In contrast, viruses using multimedia messaging services could infect all users in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating system's market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.},
  archiveprefix = {arXiv},
  arxivid = {0906.4567},
  author = {Wang, Pu and Gonz{\'{a}}lez, Marta C. and Hidalgo, C{\'{e}}sar A. and Barabasi, Albert L{\'{a}}szl{\'{o}}},
  doi = {10.1126/science.1167053},
  eprint = {0906.4567},
  isbn = {00368075},
  issn = {00368075},
  journal = {Science},
  month = {may},
  number = {5930},
  pages = {1071--1076},
  pmid = {19342553},
  title = {{Understanding the Spreading Patterns of Mobile Phone Viruses}},
  url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1167053},
  volume = {324},
  year = {2009}
}
@article{Castelvecchi2016,
  abstract = {Machine learning is becoming ubiquitous in basic research as well as in industry. But for scientists to trust it, they first need to understand what the machines are doing.},
  author = {Castelvecchi, Davide},
  doi = {10.1038/538020a},
  isbn = {0316069434},
  issn = {14764687},
  journal = {Nature},
  month = {oct},
  number = {7623},
  pages = {20--23},
  pmid = {27708329},
  title = {{Can we open the black box of AI?}},
  url = {http://www.nature.com/doifinder/10.1038/538020a},
  volume = {538},
  year = {2016}
}
@article{Mao2015,
  abstract = {The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. Here we leverage mobile call log data from C{\^{o}}te d'Ivoire to analyze the relations between its nation-wide communications network and the socio-economic dynamics of its regional economies. We introduce the CallRank indicator to quantify the relative importance of an area on the basis of call records, and show that a region's ratio of in- and out-going calls can predict its income level. We detect a communication divide between rich and poor regions of C{\^{o}}te d'Ivoire, which corresponds to existing socio-economic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.},
  author = {Mao, Huina and Shuai, Xin and Ahn, Yong Yeol and Bollen, Johan},
  doi = {10.1140/epjds/s13688-015-0053-1},
  file = {::},
  isbn = {2193-1127},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {big data analysis,developing countries,economic development,mobile phone data,network analysis,socio-economic measurement},
  month = {dec},
  number = {1},
  pages = {1--16},
  publisher = {Springer Berlin Heidelberg},
  title = {{Quantifying socio-economic indicators in developing countries from mobile phone communication data: applications to C{\^{o}}te d'Ivoire}},
  url = {http://www.epjdatascience.com/content/4/1/15},
  volume = {4},
  year = {2015}
}
@article{Dashdorj2015,
  abstract = {Every day, billions of geo-referenced data (e.g., mobile phone data records, geo-tagged social media, gps records, etc.) are generated by user activities. Such data provides inspiring insights about human activities and behaviors, the discovery of which is important in a variety of domains such as social and economic development, urban planning, and health prevention. The major challenge in those areas is that interpreting such a big stream of data requires a deep understanding of context where each activity occurs. In this study, we use a geographical information data, OpenStreetMap (OSM) to enrich such context with possible knowledge. We build a combined logical and statistical reasoning model for inferring human activities in qualitative terms in a given context. An extensive validation of the model is performed using separate data-sources in two different cities. The experimental study shows that the model is proven to be effective with a certain accuracy for predicting the context of human activity in mobile phone data records.},
  archiveprefix = {arXiv},
  arxivid = {1504.05895},
  author = {Dashdorj, Zolzaya and Sobolevsky, Stanislav and Lee, Sang Keun and Ratti, Carlo},
  doi = {10.1016/j.knosys.2017.11.038},
  eprint = {1504.05895},
  file = {::},
  issn = {09507051},
  journal = {Knowledge-Based Systems},
  keywords = {Human activity recognition,Knowledge management,Ontology,Spatial data},
  month = {apr},
  pages = {225--235},
  title = {{Deriving human activity from geo-located data by ontological and statistical reasoning}},
  url = {http://arxiv.org/abs/1504.05895 http://dx.doi.org/10.1016/j.knosys.2017.11.038},
  volume = {143},
  year = {2018}
}
@article{DjurdjevacConrad2018,
  abstract = {Human mobility always had a great influence on the spreading of cultural, social and technological ideas. Developing realistic models that allow for a better understanding, prediction and control of such coupled processes has gained a lot of attention in recent years. However, the modeling of spreading processes that happened in ancient times faces the additional challenge that available knowledge and data is often limited and sparse. In this paper, we present a new agent-based model for the spreading of innovations in the ancient world that is governed by human movements. Our model considers the diffusion of innovations on a spatial network that is changing in time, as the agents are changing their positions. Additionally, we propose a novel stochastic simulation approach to produce spatio-temporal realizations of the spreading process that are instructive for studying its dynamical properties and exploring how different influences affect its speed and spatial evolution.},
  author = {{Djurdjevac Conrad}, Nata{\v{s}}a and Helfmann, Luzie and Zonker, Johannes and Winkelmann, Stefanie and Sch{\"{u}}tte, Christof},
  doi = {10.1140/epjds/s13688-018-0153-9},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {Agent-based model,Diffusion process,Human mobility,Spreading process,Stochastic simulation algorithm},
  month = {dec},
  number = {1},
  pages = {24},
  title = {{Human mobility and innovation spreading in ancient times: a stochastic agent-based simulation approach}},
  url = {https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-018-0153-9},
  volume = {7},
  year = {2018}
}
@article{Scherrer2018,
  abstract = {As users of mobile devices make phone calls, browse the web, or use an app, large volumes of data are routinely generated that are a potentially useful source for investigating human behavior in space. However, as such data are usually collected only as a by-product, they often lack stringent experimental design and ground truth, which makes interpretation and derivation of valid behavioral conclusions challenging. Here, we propose an unsupervised, data-driven approach to identify different user types based on high-resolution human movement data collected from a smartphone navigation app, in the absence of ground truth. We capture spatio-temporal footprints of users, characterized by meaningful summary statistics, which are then used in an unsupervised step to identify user types. Based on an extensive dataset of users of the mobile navigation app Sygic in Australia, we show how the proposed methodology allows to identify two distinct groups of users: ‘travelers', visiting different areas with distinct, salient characteristics, and ‘locals', covering shorter distances and revisiting many of their locations. We verify our approach by relating user types to space use: we find that travelers and locals prefer to visit distinct, different locations in the Australian cities Sydney and Melbourne, as suggested independently by other studies. Although we use high-resolution GPS data, the proposed methodology is potentially transferable to low-resolution movement data (e.g. Call Detail Records), since we rely only on summary statistics.},
  author = {Scherrer, Luca and Tomko, Martin and Ranacher, Peter and Weibel, Robert},
  doi = {10.1140/epjds/s13688-018-0147-7},
  issn = {21931127},
  journal = {EPJ Data Science},
  keywords = {Clustering,Human mobility,Movement patterns,PCA,Unsupervised learning,User characterization},
  month = {dec},
  number = {1},
  pages = {19},
  title = {{Travelers or locals? Identifying meaningful sub-populations from human movement data in the absence of ground truth}},
  url = {https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-018-0147-7},
  volume = {7},
  year = {2018}
}
@article{Balzotti2018a,
  abstract = {In this paper we deal with the study of travel flows and patterns of people in large populated areas. Information about the movements of people is extracted from coarse-grained aggregated cellular network data without tracking mobile devices individually Mobile phone data are provided by the Italian telecommunication company TIM and consist of density profiles (i.e. the spatial distribution) of people in a given area at various instants of time. By computing a suitable approximation of the Wasserstein distance between two consecutive density profiles, we are able to extract the main directions followed by people, i.e. to understand how the mass of people distribute in space and time. The main applications of the proposed technique are the monitoring of daily flows of commuters, the organization of large events, and, more in general, the traffic management and control.},
  archiveprefix = {arXiv},
  arxivid = {1803.00814},
  author = {Balzotti, Caterina and Bragagnini, Andrea and Briani, Maya and Cristiani, Emiliano},
  doi = {10.1016/j.ifacol.2018.07.005},
  eprint = {1803.00814},
  issn = {24058963},
  journal = {IFAC-PapersOnLine},
  keywords = {Cellular data,Wasserstein distance,earth mover's distance,presence data},
  number = {9},
  pages = {25--30},
  title = {{Understanding Human Mobility Flows from Aggregated Mobile Phone Data}},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S2405896318307213},
  volume = {51},
  year = {2018}
}
@article{Huang2018,
  abstract = {Understanding how citizens interact with transportation system is a key to solving a variety of urban issues in general and traffic congestion in particular. Recently, scholars have put efforts on the pertinent work ranging from developing traffic predictors to understanding human mobility and activity patterns. Multiple types of data have been used, of which crowdsourced data (e.g. social media data) plays an essential role. Due to the limitation of traffic information extraction from social media data raised in the existing work, this paper aims to develop an approach which allows us to explore the potential influence of human activities on daily traffic congestions through linking human activities derived from geotagged tweets to the daily traffic conditions. The result of a case study of Toronto, Canada exhibits that entertainment related activities are more likely to appear during evening peak hours, while it seems that morning rush hours are less sensitive to human activities. In addition, it is learned that the activities involved in international events tend to have a long-term impact on urban traffic. This work provides a new tool for urban planners and policy makers to deal with complex urban issues effectively using low-cost social media data and sheds light on the research on analyzing urban traffic and urban dynamics based on crowdsourced data.},
  author = {Huang, Wei and Xu, Shishuo and Yan, Yingwei and Zipf, Alexander},
  doi = {10.1016/j.cities.2018.07.001},
  issn = {02642751},
  journal = {Cities},
  keywords = {Daily traffic condition,Human activity,Semantic pattern,Spatiotemporal pattern,Toronto, Canada},
  month = {jul},
  title = {{An exploration of the interaction between urban human activities and daily traffic conditions: A case study of Toronto, Canada}},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0264275118302786},
  year = {2018}
}
@article{Batran2018,
  author = {Batran, Mohammed and Mejia, Mariano Gregorio and Sekimoto, Yoshihide and Shibasaki, Ryosuke},
  doi = {10.3390/ijgi7070259},
  issn = {16130073},
  journal = {CEUR Workshop Proceedings},
  month = {jun},
  number = {7},
  pages = {1--8},
  title = {{Inference of human spatiotemporal mobility in greater Maputo by mobile phone big data mining}},
  url = {http://www.mdpi.com/2220-9964/7/7/259},
  volume = {2129},
  year = {2018}
}
@article{JENNIFFER2018,
  author = {Jenniffer, Joy and Vijaya, Samundeeswari},
  doi = {10.26634/jcs.7.2.14442},
  issn = {2277-5102},
  journal = {i-manager's Journal on Communication Engineering and Systems},
  number = {2},
  pages = {31},
  title = {{Analysing Work Tour Motifs From {GPS} Trajectory Data}},
  url = {http://www.imanagerpublications.com/article/14442},
  volume = {7},
  year = {2018}
}
@article{Liu2018,
  abstract = {Since many parents travel separately for escorting and commuting, certain hidden daily car trips may have been ignored in previous research regarding parental escort behaviors. By defining an escort-space model using the spatial relationships between home, the workplace, and school, this study focuses on the daily modal split among parental chauffeurs using data from Qujing, China, while focusing on the effects of different escort-space models: spatial aggregation, job-housing separation and school-housing separation. The descriptive statistics of parental chauffeurs' travel mode choices under the influences of these three escort-space models are presented. The statistical results demonstrate that the modal splits of parental chauffeurs perform significantly differently under these three escort-space models. Furthermore, the determinants of the daily travel mode of parental chauffeurs, including escort-spaces and other selected variables, are investigated using a multinomial logit model. A model without the escort-space model is also presented for comparison. The results show that the model with the escort-space model has a more significant goodness-of-fit than the model without the escort-space model. Both the job-housing separation and school-housing separation of parental chauffeurs result in the increase of car trips, while the usage amount of car in daily journeys is higher than that in escort trips. Moreover, car ownership, bike ownership, household income, residential location, age, gender, income, and education level all significantly impact the daily travel mode choices of parental chauffeurs. These findings can help policymakers create suitable policies to reduce excessive car trips by parental chauffeurs.},
  author = {Liu, Yang and Ji, Yanjie and Shi, Zhuangbin and He, Baohong and Liu, Qiyang},
  doi = {10.1016/j.tranpol.2018.06.004},
  issn = {1879310X},
  journal = {Transport Policy},
  keywords = {Child,Escort-space,Nearby enrollment policy,Parental chauffeurs,Travel mode choice},
  month = {oct},
  pages = {78--87},
  title = {{Investigating the effect of the spatial relationship between home, workplace and school on parental chauffeurs' daily travel mode choice}},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0967070X17306029},
  volume = {69},
  year = {2018}
}
@article{Huang2018a,
  author = {Huang, Zhengfeng and Huang, Zhaodong and Zheng, Pengjun and Xu, Wenjun},
  doi = {10.3390/info9050115},
  issn = {2078-2489},
  journal = {Information},
  month = {may},
  number = {5},
  pages = {115},
  title = {{Calibration of C-Logit-Based SUE Route Choice Model Using Mobile Phone Data}},
  url = {http://www.mdpi.com/2078-2489/9/5/115},
  volume = {9},
  year = {2018}
}
@incollection{Fiadino2018,
  address = {Cham},
  author = {Fiadino, Pierdomenico and Torrent-Moreno, Marc},
  booktitle = {Encyclopedia of Big Data Technologies},
  doi = {10.1007/978-3-319-63962-8_259-1},
  pages = {1--11},
  publisher = {Springer International Publishing},
  title = {{Big Data in Mobile Networks}},
  url = {http://link.springer.com/10.1007/978-3-319-63962-8{\_}259-1},
  year = {2018}
}
@article{Zegras2018,
  author = {Zegras, P. Christopher and Li, Menghan and Kilic, Talip and Lozano-Gracia, Nancy and Ghorpade, Ajinkya and Tiberti, Marco and Aguilera, Ana I. and Zhao, Fang},
  doi = {10.1007/s11116-017-9851-6},
  isbn = {1111601798},
  issn = {15729435},
  journal = {Transportation},
  keywords = {Dar es Salaam,Household travel survey,Response rates and biases,Smartphones,Tanzania},
  month = {mar},
  number = {2},
  pages = {335--363},
  title = {{Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam, Tanzania}},
  url = {http://link.springer.com/10.1007/s11116-017-9851-6},
  volume = {45},
  year = {2018}
}
@article{Wang2018a,
  abstract = {Passively-generated mobile phone data is emerging as a potential data source for transportation research and applications. Despite the large amount of studies based on the mobile phone data, only a few have reported the properties of such data, and documented how they have processed the data. In this paper, we describe two types of common mobile phone data: Call Details Record (CDR) data and sightings data, and propose a data processing framework and the associated algorithms to address two key issues associated with the sightings data: locational uncertainty and oscillation. We show the effectiveness of our proposed methods in addressing these two issues compared to the state of art algorithms in the field. We also demonstrate that without proper processing applied to the data, the statistical regularity of human mobility patterns—a key, significant trait identified for human mobility—is over-estimated. We hope this study will stimulate more studies in examining the properties of such data and developing methods to address them. Though not as glamorous as those directly deriving insights on mobility patterns (such as statistical regularity), understanding properties of such data and developing methods to address them is a fundamental research topic on which important insights are derived on mobility patterns.},
  author = {Wang, Feilong and Chen, Cynthia},
  doi = {10.1016/j.trc.2017.12.003},
  issn = {0968090X},
  journal = {Transportation Research Part C: Emerging Technologies},
  keywords = {Human mobility trajectory,Incremental clustering method,Locational uncertainty,Oscillation problem,Representativeness issue,Statistical regularity,Time-window-based method},
  month = {feb},
  pages = {58--74},
  title = {{On data processing required to derive mobility patterns from passively-generated mobile phone data}},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0968090X17303637},
  volume = {87},
  year = {2018}
}
@incollection{Wang2018,
  author = {Wang, De and Zhong, Weijing and Yin, Zhenxuan and Xie, Dongcan and Luo, Xiao},
  doi = {10.1007/978-3-319-51929-6_13},
  pages = {239--254},
  title = {{Spatio-temporal Dynamics of Population in Shanghai: A Case Study Based on Cell Phone Signaling Data}},
  url = {http://link.springer.com/10.1007/978-3-319-51929-6{\_}13},
  year = {2018}
}
@incollection{Xu2018,
  author = {Xu, Yang and Shaw, Shih-Lung and Lu, Feng and Chen, Jie and Li, Qingquan},
  doi = {10.1007/978-3-319-73247-3_3},
  pages = {41--65},
  title = {{Uncovering the Relationships Between Phone Communication Activities and Spatiotemporal Distribution of Mobile Phone Users}},
  url = {http://link.springer.com/10.1007/978-3-319-73247-3{\_}3},
  year = {2018}
}
@article{Beck2018,
  abstract = {Collaboration is essential for effective performance by groups of robots in disaster response settings. Here we are particularly interested in heterogeneous robots that collaborate in complex scenarios with incomplete, dynamically changing information. In detail, we consider an automated victim search setting, where unmanned aerial vehicles (UAVs) with different capabilities work together to scan for mobile phones and find and provide information about possible victims near these phone locations. The state of the art for such collaboration is robot control based on independent planning for robots with different tasks and typically incorporates uncertainty with only a limited scope. In contrast, in this paper, we take into account complex relations between robots with different tasks. As a result, we create a joint, full-horizon plan for the whole robot team by optimising over the uncertainty of future information gain using an online planner with hindsight optimisation. This joint plan is also used for further optimisation of individual UAV paths based on the long-term plans of all robots. We evaluate our planner's performance in a realistic simulation environment based on a real disaster and find that our approach finds victims 25{\%} faster compared to current state-of-the-art approaches.},
  author = {Beck, Zolt{\'{a}}n and Teacy, W. T.Luke and Rogers, Alex and Jennings, Nicholas R.},
  doi = {10.1016/j.robot.2017.09.014},
  isbn = {0921-8890},
  issn = {09218890},
  journal = {Robotics and Autonomous Systems},
  keywords = {Hindsight optimisation,Multi-robot teams,Particle filter,Path planning,Search and rescue,Task allocation},
  month = {feb},
  pages = {251--266},
  title = {{Collaborative online planning for automated victim search in disaster response}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S0921889016307515},
  volume = {100},
  year = {2018}
}
@article{Koide2018,
  author = {Koide, Satoshi and Tadokoro, Yukihiro and Yoshimura, Takayoshi and Xiao, Chuan and Ishikawa, Yoshiharu},
  doi = {10.1145/3200200},
  issn = {23740353},
  journal = {ACM Transactions on Spatial Algorithms and Systems},
  keywords = {Spatiotemporal indexing,network-constrained trajectories,string algorithms},
  month = {jun},
  number = {1},
  pages = {1--41},
  title = {{Enhanced Indexing and Querying of Trajectories in Road Networks via String Algorithms}},
  url = {http://dl.acm.org/citation.cfm?doid=3232637.3200200},
  volume = {4},
  year = {2018}
}
@article{Astarita2018,
  author = {Astarita, Vittorio and Festa, Demetrio Carmine},
  doi = {10.1016/j.procs.2018.07.191},
  isbn = {0000000000},
  issn = {18770509},
  journal = {Procedia Computer Science},
  number = {June},
  pages = {407--414},
  title = {{Mobile Systems applied to Traffic Management and Safety : a state of the art DRAFT 2 final Electronic preprint Mobile Systems applied to Traffic Management and Safety : a state of the art}},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S1877050918311566},
  volume = {134},
  year = {2018}
}
@inproceedings{Neal2018,
  author = {Neal, Tempestt J and Woodard, Damon L},
  booktitle = {2018 IEEE 4th International Conference on Identity, Se- curity, and Behavior Analysis (ISBA)},
  doi = {10.1109/ISBA.2018.8311459},
  isbn = {978-1-5386-2248-3},
  month = {jan},
  pages = {1--8},
  publisher = {IEEE},
  title = {{A Gender-Specific Behavioral Analysis of Mobile Device Usage Data}},
  url = {http://ieeexplore.ieee.org/document/8311459/},
  year = {2018}
}
@article{Schumacher2001,
  author = {Schumacher, P and Morahan-Martin, J},
  journal = {Computers in Human Behavior},
  title = {{Gender, internet and computer attitudes and experiences}},
  volume = {17},
  year = {2001}
}
@book{salganik2017bit,
  title = {Bit by Bit: Social Research in the Digital Age},
  author = {Salganik, M.J.},
  isbn = {9781400888184},
  url = {https://books.google.cl/books?id=RqMnDwAAQBAJ},
  year = {2017},
  publisher = {Princeton University Press}
}
@techreport{Yvesalexandre2016,
  author = {{De Montjoye}, Yves-Alexandre and Blondel, Vincent and Canright, Geoffrey and Gambs, Sebastien and Garcia, Manuel and Kendall, Jake and Oliver, Nuria and Rutherford, Alex and Smoreda, Zbigniew},
  booktitle = {MIT working paper},
  publisher = {Erik Wetter},
  title = {{Privacy-conscientious use of mobile phone data}},
  url = {http://openscholar.mit.edu/sites/default/files/bigdataworkshops/files/draft{\_}modelsformobilephonedatasharing.pdf},
  institution = {Massachussetts Institute of Technology},
  year = {2016}
}
@article{YYoshimura2016,
  abstract = {In this article, we introduce the method of urban association rules and its uses for extracting frequently appearing combinations of stores that are visited together to characterize shoppers? behaviors. The Apriori algorithm is used to extract the association rules (i.e. if -{\textgreater} result) from customer transaction datasets in a market-basket analysis. An application to our large-scale and anonymized bank card transaction dataset enables us to output linked trips for shopping all over the city: the method enables us to predict the other shops most likely to be visited by a customer given a particular shop that was already visited as an input. In addition, our methodology can consider all transaction activities conducted by customers for a whole city. This approach enables us to uncover not only simple linked trips such as transition movements between stores but also the edge weight for each linked trip in the specific district. Thus, the proposed methodology can complement conventional research methods. Enhancing understanding of people?s shopping behaviors could be useful for city authorities and urban practitioners for effective urban management. The results also help individual retailers to rearrange their services by accommodating the needs of their customers? habits to enhance their shopping experience.},
  author = {Yoshimura, Yuji and Sobolevsky, Stanislav and {Bautista Hobin}, Juan N. and Ratti, Carlo and Blat, Josep},
  doi = {10.1177/0265813516676487},
  issn = {23998091},
  journal = {Environment and Planning B: Urban Analytics and City Science},
  keywords = {Barcelona,Shopping behaviors,association rule,transaction data},
  number = {2},
  pages = {367--385},
  title = {{Urban association rules: Uncovering linked trips for shopping behavior}},
  volume = {45},
  year = {2018}
}
@article{Sulis2018,
  abstract = {In this paper, we propose a computational approach to Jane Jacobs' concept of diversity and vitality, analyzing new forms of spatial data to obtain quantitative measurements of urban qualities frequently employed to evaluate places. We use smart card data collected from public transport to calculate a diversity value for each research unit. Diversity is composed of three dynamic attributes: intensity, variability, and consistency, each measuring different temporal variations of mobility flows. We then apply a regression model to establish the relationship between diversity and vitality, using Twitter data as a proxy for human activity in urban space. Final results (also validated using data sourced from OpenStreetMap) unveil which are the most vibrant areas in London.},
  author = {Sulis, Patrizia and Manley, Ed and Zhong, Chen and Batty, Michael},
  doi = {10.5311/JOSIS.2018.16.384},
  file = {::},
  issn = {1948-660X},
  journal = {Journal of Spatial Information Science},
  month = {jun},
  number = {16},
  pages = {137--162},
  title = {{Using mobility data as proxy for measuring urban vitality}},
  url = {http://josis.org/index.php/josis/article/view/384},
  volume = {2018},
  year = {2018}
}
@inproceedings{Mejova2018,
  address = {New York, New York, USA},
  author = {Mejova, Yelena and Gandhi, Harsh Rajiv and Rafaliya, Tejas Jivanbhai and Sitapara, Mayank Rameshbhai and Kashyap, Ridhi and Weber, Ingmar},
  booktitle = {Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS)  - COMPASS '18},
  doi = {10.1145/3209811.3212698},
  isbn = {9781450358163},
  keywords = {Facebook,gender gaps,internet access,now-casting},
  pages = {1--5},
  publisher = {ACM Press},
  title = {{Measuring Subnational Digital Gender Inequality in India through Gender Gaps in Facebook Use}},
  url = {http://dl.acm.org/citation.cfm?doid=3209811.3212698},
  year = {2018}
}
@article{Beiro2018,
  abstract = {The social inclusion aspects of shopping malls and their effects on our understanding of urban spaces have been a controversial argument largely discussed in the literature. Shopping malls offer an open, safe and democratic version of the public space. Many of their detractors suggest that malls target their customers in subtle ways, promoting social exclusion. In this work, we analyze whether malls offer opportunities for social mixing by analyzing the patterns of shopping mall visits in a large Latin-American city: Santiago de Chile. We use a large XDR (Data Detail Records) dataset from a telecommunication company to analyze the mobility of {\$}387,152{\$} cell phones around {\$}16{\$} large malls in Santiago de Chile during one month. We model the influx of people to malls in terms of a gravity model of mobility, and we are able to predict the customer profile distribution of each mall, explaining it in terms of mall location, the population distribution, and mall size. Then, we analyze the concept of social attraction, expressed as people from low and middle classes being attracted by malls that target high-income customers. We include a social attraction factor in our model and find that it is negligible in the process of choosing a mall. We observe that social mixing arises only in peripheral malls located farthest from the city center, which both low and middle class people visit. Using a co-visitation model we show that people tend to choose a restricted profile of malls according to their socio-economic status and their distance from the mall. We conclude that the potential for social mixing in malls could be capitalized by designing public policies regarding transportation and mobility.},
  archiveprefix = {arXiv},
  arxivid = {1802.00041},
  author = {Beir{\'{o}}, Mariano G. and Bravo, Loreto and Caro, Diego and Cattuto, Ciro and Ferres, Leo and Graells-Garrido, Eduardo},
  eprint = {1802.00041},
  journal = {EPJ Data Science},
  title = {{Shopping Mall Attraction and Social Mixing at a City Scale}},
  url = {http://arxiv.org/abs/1802.00041},
  volume = {(in press)},
  year = {2018}
}
@article{Barbosa2018,
  abstract = {Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.},
  archiveprefix = {arXiv},
  arxivid = {1710.00004},
  author = {Barbosa, Hugo and Barthelemy, Marc and Ghoshal, Gourab and James, Charlotte R. and Lenormand, Maxime and Louail, Thomas and Menezes, Ronaldo and Ramasco, Jos{\'{e}} J. and Simini, Filippo and Tomasini, Marcello},
  doi = {10.1016/j.physrep.2018.01.001},
  eprint = {1710.00004},
  issn = {03701573},
  journal = {Physics Reports},
  keywords = {Human dynamics,Human mobility,Origin–destination matrices,Random walks},
  month = {mar},
  pages = {1--74},
  title = {{Human mobility: Models and applications}},
  url = {http://linkinghub.elsevier.com/retrieve/pii/S037015731830022X},
  volume = {734},
  year = {2018}
}
@article{Zagatti2018,
  abstract = {The rapid, unplanned urbanisation in Haiti creates a series of urban mobility challenges which can contribute to job market fragmentation and decrease the quality of life in the city. Data on population and job distributions, and on home-work commuting patterns in major urban centres are scarce. The most recent census took place in 2003 and events such as the 2010 earthquake have caused major redistributions of the population. In this data scarce context, our work takes advantage of nationwide de-identified Call Detail Records (CDR) from the main mobile operator in the country to investigate night and daytime populations densities and commuting patterns. We use a non-supervised learning algorithm to identify meaningful locations for individuals. These locations are then labelled according to a scoring criteria. The labelled locations are distributed in a grid with cells measuring 500 × 500 m in order to aggregate the individual level data and to create origin-destination matrices of weighted connections between home and work locations. The results suggest that labor markets are fragmented in Haiti. The two main urban centres, Port-au-Prince and Cap-Ha{\"{i}}tien suffer from low employment accessibility as measured by the percentage of the population that travels beyond their identified home cluster (1 km radius) during the day. The data from the origin-destination matrices suggest that only 42 and 40 percent of the population are considered to be commuters in Port-au-Prince and Cap-Ha{\"{i}}tien respectively.},
  author = {Zagatti, Guilherme Augusto and Gonzalez, Miguel and Avner, Paolo and Lozano-Gracia, Nancy and Brooks, Christopher J. and Albert, Maximilian and Gray, Jonathan and Antos, Sarah Elizabeth and Burci, Priya and zu Erbach-Schoenberg, Elisabeth and Tatem, Andrew J. and Wetter, Erik and Bengtsson, Linus},
  doi = {10.1016/j.deveng.2018.03.002},
  issn = {23527285},
  journal = {Development Engineering},
  keywords = {CDR,Call detail records,Commuting,Non-supervised learning,Urban planning,Urbanisation},
  pages = {133--165},
  title = {{A trip to work: Estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR}},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S2352728517300866},
  volume = {3},
  year = {2018}
}
@incollection{Karatsoli2018,
  author = {Karatsoli, Maria and Nathanail, Eftihia},
  doi = {10.1007/978-3-319-74454-4_52},
  pages = {540--550},
  title = {{A Thorough Review of Big Data Sources and Sets Used in Transportation Research}},
  url = {http://link.springer.com/10.1007/978-3-319-74454-4{\_}52},
  year = {2018}
}
@incollection{Li2018,
  author = {Li, Miaoyi and Wu, Nawei and Tang, Xiaoyong and Lu, Jia},
  doi = {10.1007/978-3-319-51929-6_19},
  pages = {359--387},
  title = {{Understanding Job-Housing Relationship from Cell Phone Data Based on Hadoop}},
  url = {http://link.springer.com/10.1007/978-3-319-51929-6{\_}19},
  year = {2018}
}
@incollection{Yang2019,
  author = {Yang, Chao and Zhang, Yuliang and Ukkusuri, Satish V. and Zhu, Rongrong},
  doi = {10.1007/978-3-319-75862-6_9},
  pages = {217--232},
  title = {{Mobility Pattern Identification Based on Mobile Phone Data}},
  url = {http://link.springer.com/10.1007/978-3-319-75862-6{\_}9},
  year = {2019}
}
@book{BangladeshUniversityofEngineeringandTechnology.DepartmentofComputerScienceandEngineering,
  abstract = {"IEEE Catalog Number: CFP15A38-ART"--PDF copyright page. Annotation Addressing and location management Cellular and broadband wireless nets Cognitive radio networking Congestion control Cross layer design and optimization Cyber physical systems and networking Data centers Data reduction, inference, and signal processing Delay disruption tolerant networks Denial of service Embedded software for sensor networks Energy harvesting Experience with real world applications Experimental results from operational networks or network applications.},
  author = {{Bangladesh University of Engineering and Technology. Department of Computer Science and Engineering} and {Bangladesh University of Engineering and Technology. ACM Chapter} and {IEEE Communications Society. Bangladesh Chapter} and {Institute of Electrical and Electronics Engineers}},
  isbn = {9781479981250},
  title = {{Proceedings of 2015 International Conference on Networking Systems and Security (NSysS) : 5-7 January, 2015, Dhaka, Bangladesh}}
}
@incollection{Pinjari,
  author = {Pinjari, Abdul Rawoof},
  booktitle = {A Handbook of Transport Economics},
  doi = {10.4337/9780857930873.00017},
  publisher = {Edward Elgar Publishing},
  title = {{Activity-based Travel Demand Analysis}},
  url = {http://www.elgaronline.com/view/9781847202031.00017.xml}
}
@book{InstituteofElectricalandElectronicsEngineersd,
  abstract = {The conference was collocated with the IEEE International Workshop on Intelligent Energy Systems (IWIES)},
  author = {{Institute of Electrical and Electronics Engineers} and Systems, Man and Cybernetics Society and {IEEE International Conference on Systems}, Man and Cybernetics 2014.10.05-08 San Diego and {IEEE SMC 2014.10.05-08 San Diego}, Calif.},
  isbn = {9781479938407},
  title = {{IEEE International Conference on Systems, Man and Cybernetics (SMC), 2014 5-8 Oct. 2014, San Diego, CA, USA ; proceedings}}
}
@book{InstituteofElectricalandElectronicsEngineers.,
  author = {{Institute of Electrical and Electronics Engineers.} and {IEEE Communications Society.}},
  issn = {2150-329X},
  publisher = {Institute of Electrical and Electronics Engineers},
  title = {{International Global Information Infrastructure Symposium.}}
}
@incollection{Evans-Cowley,
  author = {Evans-Cowley, Jennifer S. and Kubinski, Brittany},
  booktitle = {Emerging Issues, Challenges, and Opportunities in Urban E-Planning},
  doi = {10.4018/978-1-4666-8150-7.ch002},
  pages = {33--45},
  title = {{There's an App for That:}},
  url = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-4666-8150-7.ch002}
}
@book{InstituteofElectricalandElectronicsEngineers.SeattleSection,
  abstract = {"IEEE Catalog Number: CFP14GHT"--PDF copyright page.},
  author = {{Institute of Electrical and Electronics Engineers. Seattle Section} and {Institute of Electrical and Electronics Engineers. Santa Clara Valley Section} and {Institute of Electrical and Electronics Engineers. Region 6} and {Institute of Electrical and Electronics Engineers}},
  isbn = {9781479971930},
  title = {{Proceedings of the Fourth IEEE Global Humanitarian Technology Conference : GHTC 2014 : October 10-13, 2014 : San Jose/Silicon Valley, California USA : [Technology for the Benefit of Humanity]}}
}
@incollection{Yokus,
  abstract = {This study examines the views of undergraduate students in Education Faculty related to mobile learning and reveals their mobile usage behaviors. Mobile usage behaviors include students' view about effectiveness of mobile learning, their mobile design preferences, use of mobile device for purpose of learning, the activity types conducted with mobile devices and their mobile usage frequency. It comes out that university students have very positive attitudes towards mobile learning and they think that m-learning is a really effective learning method. However, mobile devices are used mostly for two purposes: socialization and entertainment. University students agree that mobile learning removes constraints like time and space dependency. They view simplicity and fluency as the prerequisites for a mobile application. Their behaviors are infrequent when it comes to the use of mobile devices for accessing library, reading article, doing homework and note-taking. Their readiness for m-learning is considerably high and they have necessary skills for this learning form. {\textcopyright} 2017 by IGI Global. All rights reserved.},
  author = {Yokuş, G{\"{u}}rol and Yelken, Tuğba Yanpar},
  doi = {10.4018/978-1-5225-1692-7.ch015},
  isbn = {9781522516934 (ISBN); 1522516921 (ISBN); 9781522516927 (ISBN)},
  pages = {297--324},
  title = {{The Adoption of Mobile Devices as Digital Tools for Seamless Learning}},
  url = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-1692-7.ch015}
}
@misc{Margetts,
  author = {Margetts, Helen},
  title = {{The Computational Social Science Society of the Americas | CSSSA}},
  url = {https://computationalsocialscience.org/},
  urldate = {2018-08-16}
}
@inproceedings{sampling2015,
  author = {Ricardo Baeza{-}Yates},
  title = {Incremental Sampling of Query Logs},
  booktitle = {Proceedings of the 38th International {ACM} {SIGIR} Conference on
               Research and Development in Information Retrieval, Santiago, Chile,
               August 9-13, 2015},
  pages = {1093--1096},
  year = {2015}
}
@techreport{douglas1978cultural,
  title = {Cultural bias},
  author = {Douglas, Mary},
  number = {35},
  pages = {59},
  year = {1978},
  institution = {R. Anth. Inst. of Great Britain and Ireland}
}
@book{blindspot,
  title = {Blindspot: Hidden Biases of Good People},
  author = {Banaji and Greenwald},
  publisher = {Bantam},
  pages = {272},
  year = {2016}
}
@book{bohnet2016works,
  title = {What works: Gender equality by design},
  author = {Bohnet, Iris},
  year = {2016},
  publisher = {Belknap Press, Cambridge, MA}
}
@book{chafetz1990gender,
  title = {Gender equity: An integrated theory of stability and change},
  author = {Chafetz, Janet Saltzman},
  series = {SAGE Library of Social Research},
  volume = {176},
  year = {1989},
  publisher = {Sage Publications}
}
@article{greenwald2006implicit,
  title = {Implicit bias: Scientific foundations},
  author = {Greenwald, Anthony G and Krieger, Linda Hamilton},
  journal = {California Law Review},
  volume = {94},
  number = {4},
  pages = {945--967},
  year = {2006},
  publisher = {JSTOR}
}
@techreport{olteanu2016social,
  author = {Olteanu, Alexandra and Castillo, Carlos and Diaz, Fernando and Kiciman, Emre},
  year = {2016},
  month = {01},
  number = {2886566},
  pages = {},
  title = {Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries},
  institution = {SSRN Electronic Journal}
}
@book{morgan2015counterfactuals,
  title = {Counterfactuals and causal inference},
  author = {Morgan, Stephen L and Winship, Christopher},
  year = {2015},
  publisher = {Cambridge University Press}
}
@incollection{obach09,
  author = {Obach, A. and Sadler, M.},
  title = {Cuerpo femenino, medicina y poder: reflexiones en torno a las disrupciones en la atención de salud reproductiva (Female body, medicine and power: reflections around disruptions of reproductive healthcare)},
  booktitle = {Nación golpeadora, manifestaciones y latencias de la violencia machista (Battering Nation, Manifestations and Heartbeats of Sexist Violence)},
  publisher = {Red chilena contra la violencia doméstica y sexual (Chilean network against domestic and sexual violence)},
  year = 2009
}
@article{chant2008feminisation,
  title = {The ‘feminisation of poverty’and the ‘feminisation’of anti-poverty programmes: Room for revision?},
  author = {Chant, Sylvia},
  journal = {The Journal of Development Studies},
  volume = {44},
  number = {2},
  pages = {165--197},
  year = {2008},
  publisher = {Taylor \& Francis}
}

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