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Community detection using local neighborhood in complex networks

Author

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  • Eustace, Justine
  • Wang, Xingyuan
  • Cui, Yaozu

Abstract

It is common to characterize community structure in complex networks using local neighborhood. Existing related methods fail to estimate the accurate number of nodes present in each community in the network. In this paper a community detection algorithm using local community neighborhood ratio function is proposed. The proposed algorithm predicts vertex association to a specific community using visited node overlapped neighbors. In the beginning, the algorithm detects local communities; then through iterations and local neighborhood ratio function, final communities are detected by merging close related local communities. Analysis of simulation results on real and artificial networks shows the proposed algorithm detects well defined communities in both networks by wide margin.

Suggested Citation

  • Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Community detection using local neighborhood in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 665-677.
    • Handle: RePEc:eee:phsmap:v:436:y:2015:i:c:p:665-677
    DOI: 10.1016/j.physa.2015.05.044
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    5. Zhu, Jiajing & Liu, Yongguo & Zhang, Yun & Liu, Xiaofeng & Xiao, Yonghua & Wang, Shidong & Wu, Xindong, 2017. "Exploring anti-community structure in networks with application to incompatibility of traditional Chinese medicine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 31-43.
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    7. Yang, Jin-Xuan & Zhang, Xiao-Dong, 2017. "Finding overlapping communities using seed set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 96-106.
    8. Tasgin, Mursel & Bingol, Haluk O., 2019. "Community detection using boundary nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 315-324.
    9. Nan, Dong-Yang & Yu, Wei & Liu, Xiao & Zhang, Yun-Peng & Dai, Wei-Di, 2018. "A framework of community detection based on individual labels in attribute networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 523-536.
    10. Wang, Tao & Wang, Hongjue & Wang, Xiaoxia, 2015. "A novel cosine distance for detecting communities in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 21-35.
    11. Wang, Tao & Chen, Shanshan & Wang, Xiaoxia & Wang, Jinfang, 2020. "Label propagation algorithm based on node importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
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    14. Chen, Naiyue & Liu, Yun & Chen, Haiqiang & Cheng, Junjun, 2017. "Detecting communities in social networks using label propagation with information entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 788-798.

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