Social Network Analysis on Highly Aggregated Data: What Can We Find?

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 186)


Social network analysis techniques have been often used to derive useful knowledge from email and communication networks. However, most previous works considered an ideal scenario when full raw data were available for analysis. Unfortunately, such data raise privacy issues, and are often considered too valuable to be disclosed. In this paper we present the results of social network analysis of a very large volume of the telecommunication data acquired from a mobile phone operator. The data are highly aggregated, with only limited amount of information about individual connections between users. We show that even with such limited data, social network analysis methods provide valuable insights into the data and can reveal interesting patterns.


Social Network Social Network Analysis Local Cluster Online Social Network Voice Call 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznanPoland

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