title: Inferring human mobility using communication patterns.
abstract: Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel between locations: by direct observations that often involve privacy issues, e.g., tracking mobile phone locations, or by estimations from models. Typically, such models build on accurate knowledge of the population size at each location. However, when this information is not readily available, their applicability is rather limited. As mobile phones are ubiquitous, our aim is to investigate if mobility patterns can be inferred from aggregated mobile phone call data alone. Using data released by Orange for Ivory Coast, we show that human mobility is well predicted by a simple model based on the frequency of mobile phone calls between two locations and their geographical distance. We argue that the strength of the model comes from directly incorporating the social dimension of mobility. Furthermore, as only aggregated call data is required, the model helps to avoid potential privacy problems.
authors.affiliation: 1] Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland [2] Institute for Condensed Matter Physics, National Academy of Sciences of Ukraine, UA 79011 Lviv, Ukraine [3] Lorentz Institute, Leiden University, 2300 RA Leiden, The Netherlands.
authors.forename: Vasyl
authors.initials: V
authors.lastname: Palchykov
authors.affiliation: 1] Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland [2] Scientific Computing Laboratory, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia.
authors.forename: Marija
authors.initials: M
authors.lastname: Mitrović
authors.affiliation: 1] Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland [2] BK21plus Physics Division and Department of Physics, Pohang University of Science and Technology, Pohang 790-784, Republic of Korea.
authors.forename: Hang-Hyun
authors.initials: HH
authors.lastname: Jo
authors.affiliation: Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland.
authors.forename: Jari
authors.initials: J
authors.lastname: Saramäki
authors.affiliation: Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland.
authors.forename: Raj Kumar
authors.initials: RK
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D003142:Communication; D006801:Humans; D008962:Models, Theoretical; D012937:Social Mobility; D014195:Travel