Istituto di Scienza e Tecnologie dell'Informazione     
Coscia M., Giannotti F., Pedreschi D. Towards democratic group detection in complex networks. In: SBP 2012 - Social Computing, Behavioral - Cultural Modeling and Prediction. 5th International Conference (College Park, MD, USA, 3-5 April 2012). Proceedings, pp. 105 - 113. Shanchieh Jay Yang, Ariel M. Greenberg, Mica Endsley (eds.). (Lecture Notes in Computer Science, vol. 7227). Springer, 2012.
To detect groups in networks is an interesting problem with applications in social and security analysis. Many large networks lack a global community organization. In these cases, traditional partitioning algorithms fail to detect a hidden modular structure, assuming a global modular organization. We define a prototype for a simple localfirst approach to community discovery, namely the democratic vote of each node for the communities in its ego neighborhood. We create a preliminary test of this intuition against the state-of-the-art community discovery methods, and find that our new method outperforms them in the quality of the obtained groups, evaluated using metadata of two real world networks. We give also the intuition of the incremental nature and the limited time complexity of the proposed algorithm.
URL: http://link.springer.com/chapter/10.1007%2F978-3-642-29047-3_13
DOI: 10.1007/978-3-642-29047-3_13
Subject Computers and Society
Computer Applications in Social and Behavioral Sciences
Management of Computing
Information Systems
Data Mining
Knowledge Discovery
Computer Communication
Networks Information System
H.2.8 Database Management

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