Coalition, cryptography, and stability: mechanisms for coalition formation in task oriented domains
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A linear approximation method for the Shapley value
Artificial Intelligence
Efficient computation of the shapley value for centrality in networks
WINE'10 Proceedings of the 6th international conference on Internet and network economics
An approach for multi-objective categorization based on the game theory and Markov process
Applied Soft Computing
Community Discovery via Metagraph Factorization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Multi-objective community detection in complex networks
Applied Soft Computing
Topic oriented community detection through social objects and link analysis in social networks
Knowledge-Based Systems
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The community detection in social networks is important to understand the structural and functional properties of networks. In this paper we propose a coalitional game model for community detection in social networks, and use the Shapley Value in coalitional games to evaluate each individual's contribution to the closeness of connection. We then develop an iterative formula for computing the Shapley Value to improve the computation efficiency. We further propose a hierarchical clustering algorithm GAMEHC to detect communities in social networks. The effectiveness of our methods is verified by preliminary experimental result.