Abstract
The problem of detecting community structures in social networks is a complex problem of great importance in sociology, biology and computer science. Communities are characterized by dense intra-connections and comparatively sparse inter-cluster connections. The community detection problem is empirically formulated from a game theoretic point of view and solved using a Crowding based Differential Evolution algorithm adapted for detecting Nash equilibria of noncooperative games. Numerical results indicate the potential of this approach.
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Lung, R.I., Gog, A., Chira, C. (2011). A Game Theoretic Approach to Community Detection in Social Networks. In: Pelta, D.A., Krasnogor, N., Dumitrescu, D., Chira, C., Lung, R. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2011). Studies in Computational Intelligence, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24094-2_8
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DOI: https://doi.org/10.1007/978-3-642-24094-2_8
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