Abstract
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.
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Morzy, M., Forenc, K. (2013). Social Network Analysis on Highly Aggregated Data: What Can We Find?. In: Morzy, T., Härder, T., Wrembel, R. (eds) Advances in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 186. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32741-4_18
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DOI: https://doi.org/10.1007/978-3-642-32741-4_18
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