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2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (2012)
Istanbul Turkey
Aug. 26, 2012 to Aug. 29, 2012
ISBN: 978-1-4673-2497-7
pp: 227-234
P. J. McSweeney , Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
K. Mehrotra , Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
J. C. Oh , Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
ABSTRACT
The mainstream approach for community detection focuses on the optimization of a metric that measures the quality of a partition over a given network. Optimizing a global metric is akin to community assignment by a centralized decision maker. In liu of global optimization, we treat each node as a player in a hedonic game and focus on their ability to form fair and stable community structures. Application on real-world networks and a well-known benchmark demonstrates that our approach produces better results than modularity optimization.
INDEX TERMS
Communities, Nash equilibrium, Games, Optimization, Measurement, Context
CITATION

J. C. Oh, K. Mehrotra and P. J. McSweeney, "A Game Theoretic Framework for Community Detection," 2012 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining(ASONAM), Istanbul, 2012, pp. 227-234.
doi:10.1109/ASONAM.2012.47
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