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Detecting overlapping communities of weighted networks via a local algorithm

Author

Listed:
  • Chen, Duanbing
  • Shang, Mingsheng
  • Lv, Zehua
  • Fu, Yan

Abstract

Identification of communities is significant in understanding the structures and functions of networks. Since some nodes naturally belong to several communities, the study of overlapping communities has attracted increasing attention recently, and many algorithms have been designed to detect overlapping communities. In this paper, an overlapping communities detecting algorithm is proposed whose main strategies are finding an initial partial community from a node with maximal node strength and adding tight nodes to expand the partial community. Seven real-world complex networks and one synthetic network are used to evaluate the algorithm. Experimental results demonstrate that the algorithm proposed is efficient for detecting overlapping communities in weighted networks.

Suggested Citation

  • Chen, Duanbing & Shang, Mingsheng & Lv, Zehua & Fu, Yan, 2010. "Detecting overlapping communities of weighted networks via a local algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4177-4187.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:19:p:4177-4187
    DOI: 10.1016/j.physa.2010.05.046
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wu, Tao & Guo, Yuxiao & Chen, Leiting & Liu, Yanbing, 2016. "Integrated structure investigation in complex networks by label propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 68-80.
    2. Benati, Stefano & Puerto, Justo & Rodríguez-Chía, Antonio M. & Temprano, Francisco, 2022. "A mathematical programming approach to overlapping community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
    3. Cui, Yaozu & Wang, Xingyuan & Eustace, Justine, 2014. "Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 198-207.
    4. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    5. Guo, Wei-Feng & Zhang, Shao-Wu, 2016. "A general method of community detection by identifying community centers with affinity propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 508-519.
    6. Li, Junqiu & Wang, Xingyuan & Eustace, Justine, 2013. "Detecting overlapping communities by seed community in weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6125-6134.
    7. Hao Long & Xiao-Wei Liu, 2019. "A Unified Community Detection Algorithm In Large-Scale Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-19, May.
    8. Guo, Chonghui & Wang, Jiajia & Zhang, Zhen, 2014. "Evolutionary community structure discovery in dynamic weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 565-576.
    9. Li, Junqiu & Wang, Xingyuan & Cui, Yaozu, 2014. "Uncovering the overlapping community structure of complex networks by maximal cliques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 398-406.
    10. Chen, Yi & Wang, Xiaolong & Xiang, Xin & Tang, Buzhou & Chen, Qingcai & Fan, Shixi & Bu, Junzhao, 2017. "Overlapping community detection in weighted networks via a Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 790-801.
    11. Sun, Hong-liang & Ch’ng, Eugene & Yong, Xi & Garibaldi, Jonathan M. & See, Simon & Chen, Duan-bing, 2018. "A fast community detection method in bipartite networks by distance dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 108-120.
    12. Wu, Tao & Chen, Leiting & Zhong, Linfeng & Xian, Xingping, 2017. "Predicting the evolution of complex networks via similarity dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 662-672.

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