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Community Detection by Node Betweenness and Similarity in Complex Network

Author

Listed:
  • Chong Feng
  • Jianxu Ye
  • Jianlu Hu
  • Hui Lin Yuan
  • Honglei Xu

Abstract

Community detection of complex networks has always been a hot issue. With the mixed parameters μ increase in network complexity, community detection algorithms need to be improved. Based on previous work, the paper designs a novel algorithm from the perspective of node betweenness properties and gives the detailed steps of the algorithm and simulation results. We compare the proposed algorithm with a series of typical algorithms through experiments on synthetic and actual networks. Experimental results on artificial and real networks demonstrate the effectiveness and superiority of our algorithm.

Suggested Citation

  • Chong Feng & Jianxu Ye & Jianlu Hu & Hui Lin Yuan & Honglei Xu, 2021. "Community Detection by Node Betweenness and Similarity in Complex Network," Complexity, Hindawi, vol. 2021, pages 1-13, July.
  • Handle: RePEc:hin:complx:9986895
    DOI: 10.1155/2021/9986895
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    Cited by:

    1. Yanjie Xu & Tao Ren & Shixiang Sun, 2022. "Community Detection Based on Node Influence and Similarity of Nodes," Mathematics, MDPI, vol. 10(6), pages 1-15, March.

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