Inferring human mobility using communication patterns View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-08-22

AUTHORS

Vasyl Palchykov, Marija Mitrović, Hang-Hyun Jo, Jari Saramäki, Raj Kumar Pan

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. More... »

PAGES

6174

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep06174

DOI

http://dx.doi.org/10.1038/srep06174

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039196472

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25146347


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206 Institute for Condensed Matter Physics, National Academy of Sciences of Ukraine, UA 79011, Ukraine, Lviv
207 Lorentz Institute, Leiden University, 2300 RA, Leiden, The Netherlands
208 rdf:type schema:Organization
209 grid-institutes:grid.5373.2 schema:alternateName Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland
210 schema:name Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, P.O. Box 12200, FI-00076, Finland
211 rdf:type schema:Organization
 




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