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Communities detection in social network based on local edge centrality

Author

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  • Li, Xuequn
  • Zhou, Shuming
  • Liu, Jiafei
  • Lian, Guanqin
  • Chen, Gaolin
  • Lin, Chen-Wan

Abstract

Centrality measurement and community detection in complex social network are important in understanding network structures and analyzing network characteristics. In view of the importance of link strength weighting, a new centrality measurement of edge, called Local Edge Centrality (shortly, LEC), is proposed from a local perspective. Furthermore, we propose a new method for communities detection in social network, called Communities Detection based on LEC (shortly, CD-LEC), based on the idea of finding boundaries of community by the aid of centrality indices of edge LEC. The presented method utilizes the divisive method to obtain an initial partition of the network and then employs the modularity optimization to get the final partition of the network. To show the effectiveness of the proposed method, we empirically analyze this strategy on the real-world and artificial networks.

Suggested Citation

  • Li, Xuequn & Zhou, Shuming & Liu, Jiafei & Lian, Guanqin & Chen, Gaolin & Lin, Chen-Wan, 2019. "Communities detection in social network based on local edge centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    • Handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119309173
    DOI: 10.1016/j.physa.2019.121552
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    Citations

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    Cited by:

    1. Aghaalizadeh, Saeid & Afshord, Saeid Taghavi & Bouyer, Asgarali & Anari, Babak, 2021. "A three-stage algorithm for local community detection based on the high node importance ranking in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    2. Shang, Ronghua & Zhang, Weitong & Zhang, Jingwen & Feng, Jie & Jiao, Licheng, 2022. "Local community detection based on higher-order structure and edge information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    3. Sahar Bakhtar & Hovhannes A. Harutyunyan, 2022. "A new metric to compare local community detection algorithms in social networks using geodesic distance," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2809-2831, November.

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