• DocumentCode
    2775738
  • Title

    Social Event Detection in Massive Mobile Phone Data Using Probabilistic Location Inference

  • Author

    Traag, V.A. ; Browet, A. ; Calabrese, F. ; Morlot, F.

  • Author_Institution
    ICTEAM, Univ. Catholique de Louvain, Louvain-la-Neuve, Belgium
  • fYear
    2011
  • fDate
    9-11 Oct. 2011
  • Firstpage
    625
  • Lastpage
    628
  • Abstract
    The unprecedented amount of data from mobile phones creates new possibilities to analyze various aspects of human behavior. Over the last few years, much effort has been devoted to studying the mobility patterns of humans. In this paper we will focus on unusually large gatherings of people, i.e. unusual social events. We introduce the methodology of detecting such social events in massive mobile phone data, based on a Bayesian location inference framework. More specifically, we also develop a framework for deciding who is attending an event. We demonstrate the method on a few examples. Finally, we discuss some possible future approaches for event detection, and some possible analyses of the detected social events.
  • Keywords
    Bayes methods; behavioural sciences computing; inference mechanisms; mobile computing; social sciences computing; Bayesian location inference framework; human behavior analysis; massive mobile phone data; mobility pattern; probabilistic location inference; social event detection; Antennas; Cities and towns; Event detection; Humans; Mobile communication; Mobile handsets; Probabilistic logic; location inference; mobile phone; social event detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011 IEEE Third International Conference on
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4577-1931-8
  • Type

    conf

  • DOI
    10.1109/PASSAT/SocialCom.2011.133
  • Filename
    6113183