arXiv:cs/0702048v1 [cs.CY] 8 Feb 2007 Finding Community Structure in Mega-scale Social Networks Ken Wakita Tokyo Institute of Technology 2-12-1 Ookayama, Meguro-ku Tokyo 152-8552, Japan wakita@is.titech.ac.jp Toshiyuki Tsurumi Tokyo Institute of Technology...
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arXiv:cs/0702048v1 [cs.CY] 8 Feb 2007 Finding Community Structure in Mega-scale Social Networks Ken Wakita Tokyo Institute of Technology 2-12-1 Ookayama, Meguro-ku Tokyo 152-8552, Japan wakita@is.titech.ac.jp Toshiyuki Tsurumi Tokyo Institute of Technology 2-12-1 Ookayama, Meguro-ku Tokyo 152-8552, Japan tsurumi2@is.titech.ac.jp ABSTRACT Community analysis algorithm proposed by Clauset, New- man, and Moore (CNM algorithm) finds community struc- ture in social networks. Unfortunately, CNM algorithm does not scale well and its use is practically limited to networks whose sizes are up to 500,000 nodes. The paper identifies that this inefficiency is caused from merging communities in unbalanced manner. The paper introduces three kinds of metrics (consolidation ratio) to control the process of com- munity analysis trying to balance the sizes of the commu- nities being merged. Three flavors of CNM algorithms are built incorporating those metrics. The proposed techniques are tested using data
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