CDPM: Finding and Evaluating Community Structure in Social Networks

Authors:
Li Wan;Jianxin Liao;Xiaomin Zhu
Affiliations:
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876 and EBUPT Information Technology Co., Ltd, Beijing, China 100 ...;State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876 and EBUPT Information Technology Co., Ltd, Beijing, China 100 ...;State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876 and EBUPT Information Technology Co., Ltd, Beijing, China 100 ...
Venue:
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Year:
2008

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Abstract

In this paper we proposed a CDPM (Clique Directed Percolation Method) algorithm, which clusters tightly cohesive cliques as cluster atoms and merge the cluster atoms into communities under the direction of a proposed object function, namely Structure Silhouette Coefficient (SSC). SSC could measure the quality of community divisions which allows communities share actors. Experiments demonstrate our algorithm can divide social networks into communities at a higher quality than compared algorithms.