Conference Proceeding Article
Communities typically capture homophily as people of the same community share many common features. This paper is motivated by the problem of community detection in social networks, as it can help improve our understanding of the network topology. Given the selfish nature of humans to align with like-minded people, we employ game theoretic models and algorithms to detect communities in this paper. Specifically, we employ coordination games to represent interactions between individuals in a social network. We provide a novel and scalable two phased algorithm NashOverlap to compute an accurate overlapping community structure in the given network. We evaluate our algorithm against the best existing methods for community detection and show that our algorithm improves significantly on benchmark networks with respect to standard normalised mutual information measure.
Theory and Algorithms
Intelligent Systems and Decision Analytics
Proceedings on the 22nd European Conference on Artificial Intelligence: ECAI 2016, The Hague, Netherlands, 2016 August 29 - September 2
City or Country
ARAVA, Radhika and Pradeep VARAKANTHAM.
Detecting communities using coordination games: A short paper. (2016). Proceedings on the 22nd European Conference on Artificial Intelligence: ECAI 2016, The Hague, Netherlands, 2016 August 29 - September 2. 285, 1752-1753. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3616
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