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Finding community structure in mega-scale social networks: [extended abstract]

9 years 10 months ago
Finding community structure in mega-scale social networks: [extended abstract]
[Extended Abstract] 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 Community analysis algorithm proposed by Clauset, Newman, and Moore (CNM algorithm) finds community structure 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. We show that this inefficiency is caused from merging communities in unbalanced manner and that a simple heuristics that attempts to merge community structures in a balanced manner can dramatically improve community structure analysis. The proposed techniques are tested using data sets obtained from existing social networking service that hosts 5.5 million users. We have tested three three variations of the heuristics. The fastest method processes a SNS friendship network wit...
Ken Wakita, Toshiyuki Tsurumi
Added 21 Nov 2009
Updated 21 Nov 2009
Type Conference
Year 2007
Where WWW
Authors Ken Wakita, Toshiyuki Tsurumi
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