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Leader-aware community detection in complex networks

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Abstract

Community structures are very common in complex networks. Detecting these communities is important for understanding the hidden features of networks. Besides, each community usually has one leader, which presents its significant influence over the whole community. However, most existing methods just focus on the problem of graph clustering, ignoring the role of community leaders. To solve this problem, in this paper, we propose a novel leader-aware community detection algorithm, which can find community structures as well as leaders of each community. This algorithm measures the leadership of each node and lets each one adhere to its local leader, forming dependence trees. Once all dependence trees are definitely settled, the community structures emerge because one tree actually is a cluster. Additionally, each root node of the tree is exactly the leader of corresponding community. This method can quickly determine the belonging of each node. Experimental results on real-world and benchmark networks demonstrate the effectiveness and the efficiency of our algorithm compared with other state-of-the-art approaches.

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Acknowledgements

The work was supported in part by the National Science Foundation of China Grants 61672417, 61876138, 61602354 and 61472299, Natural Science Basic Research Plan in Shaanxi Province of China Grants 2017JM6045 and the Fundamental Research Funds for the Central Universities of China, Science and Technology Foundation of Shenzhen City Grants JCYJ20170816100845994. Any opinions, findings and conclusions expressed here are those of the authors and do not necessarily reflect the views of the funding agencies.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, China

    Heli Sun, Hongxia Du, Yang Li, Zhongbin Sun, Liang He, Xiaolin Jia & Zhongmeng Zhao

  2. Xi’an Jiaotong University Shenzhen Research School, Shenzhen, 518057, Guangdong, China

    Heli Sun & Zhongbin Sun

  3. Shaanxi Province Key Laboratory of Computer Networks, Xi’an Jiaotong University, Xi’an, China

    Heli Sun

  4. School of Computer Science and Technology, Xidian University, Xi’an, Shaanxi, China

    Jianbin Huang

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  1. Heli Sun
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Correspondence to Jianbin Huang.

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Sun, H., Du, H., Huang, J. et al. Leader-aware community detection in complex networks. Knowl Inf Syst 62, 639–668 (2020). https://doi.org/10.1007/s10115-019-01362-1

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