Detecting anomalous behaviors using structural properties of social networks

Authors:
Yaniv Altshuler;Michael Fire;Erez Shmueli;Yuval Elovici;Alfred Bruckstein;Alex (Sandy) Pentland;David Lazer
Affiliations:
MIT Media Lab;Deutsche Telekom Lab, Department of Information Systems Engineering, Ben-Gurion University, Israel;MIT Media Lab;Deutsche Telekom Lab, Department of Information Systems Engineering, Ben-Gurion University, Israel;Computer Science Department, Technion --- Israeli Institute of Technology, Israel;MIT Media Lab;College of Computer and Information Science & Department of Political Science, Northeastern University
Venue:
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Year:
2013

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Abstract

In this paper we discuss the analysis of mobile networks communication patterns in the presence of some anomalous "real world event". We argue that given limited analysis resources (namely, limited number of network edges we can analyze), it is best to select edges that are located around 'hubs' in the network, resulting in an improved ability to detect such events. We demonstrate this method using a dataset containing the call log data of 3 years from a major mobile carrier in a developed European nation.