Journal of Jilin University Science Edition
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FENG Chengqiang, ZUO Wanli, WANG Ying
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Abstract: In order to quickly and accurately partition the community of large\|scale social networks which were increasingly complicated, we proposed an improved algorithm based on similarity voting to replace the underlying partition of Louvain algorithm. It solved the shortcomings of Louvain algorithm such as slow convergence in the bottom partitioning and large number of double counting, which made the community partition more rapidly. The experimental results from real social network data show that compared with the Louvain algorithm, the efficiency of the improved algorithm is much higher, with less number of communities partitioned, and the community structure is more compact in the case of keeping the modularity basically unchanged.
Key words: community partition, similarity voting, social network, Louvain algorithm, modularity, community structure, number of communities
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FENG Chengqiang, ZUO Wanli, WANG Ying. Improved Community Partition Algorithm Based on Similarity Voting[J].Journal of Jilin University Science Edition, 2018, 56(3): 601-609.
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http://xuebao.jlu.edu.cn/lxb/EN/Y2018/V56/I3/601
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