Inferring human mobility patterns from anonymized mobile communication usage

Yuzuru Tanahashi, James R. Rowland, Stephen North, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Anonymized Call Detail Records (CDRs) contain positional information of large populations and therefore have been extensively analyzed to understand human mobility. Due to the temporally sparse and spatially coarse nature of the data, most of these studies have focused on primitive aspects of movements such as travel distance and speed. Incorporating underlying geographic information in these analyses would allow analysts to put these movements into context and to gain deeper insight into how metropolitan areas function. In this paper, we present a set of procedures for inferring mobile users' mobility patterns while retaining the context of underlying geography. We apply these methods to our case study on New York City anonymized CDRs. We find that our methods verify current areal semantics and commuting rush-hour patterns, and we also derive further implications regarding geographic, demographic, and other effects on human mobility.

Original languageEnglish (US)
Title of host publication10th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2012 - Proceedings
Pages151-160
Number of pages10
DOIs
StatePublished - Dec 1 2012
Event10th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2012 - Bali, Indonesia
Duration: Dec 3 2012Dec 5 2012

Other

Other10th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2012
CountryIndonesia
CityBali
Period12/3/1212/5/12

Keywords

  • call detail records
  • data mining
  • human mobility
  • mobile computing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Tanahashi, Y., Rowland, J. R., North, S., & Ma, K-L. (2012). Inferring human mobility patterns from anonymized mobile communication usage. In 10th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2012 - Proceedings (pp. 151-160) https://doi.org/10.1145/2428955.2428988