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
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;
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
DOI :
10.1109/PASSAT/SocialCom.2011.133