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Identification of Key Nodes in Directed Network Based on Overlapping Community Structure

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Abstract

Key nodes identification is an important way to analyze and understand the characteristics, structure, and functions of the complex network. In this paper, links in complex networks are taken as the basic unit, and the overlapping community in complex networks is obtained through the clustering analysis of links. Then, the importance of the node is judged according to the number of associations containing the node and the weight value of the association in the network, because the nodes Shared between communities have more influence on the functional structure of the network. Finally, the method is applied to rank the importance of nodes in IEEE standard 300 node system, and the results are verified by network conductivity. The comparison with the results of the Betweenness algorithm, HITS algorithm and Pagepank algorithm shows that the method presented in this paper can effectively identify the key nodes from the complex network.

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Funding

This work is supported partially by Science and Technology Project of Jilin Provincial Department of Education in the 13th Five-year Plan Period (JJKH20190643KJ) and (JJKH20200042KJ), partially by the Project of Development and Reform Commission of Jilin Province (2019C058-1), partially by the Youth development fund project of Beihua university: (2017QNJJL04), partially by School-enterprise cooperative education program of Jilin Province (201801060050), partially by education and teaching reform project of Beihua University(XJYB2019047, XJZD2019024), partially by “Golden Class” Construction Project of Beihua University “VC++ program design and data structure” and “Signals and Systems cross-school joint gold course construction,” partially by educational science planning project of Jilin Province(GH20272), partially by higher education teaching reform of Jilin Province “Research and practice of information identification course module teaching content reform.”

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Authors and Affiliations

  1. College of Electrical and Information Engineering, Beihua University, Jilin, China; College of Communication Engineering, Jilin University, Changchun, China

    Qingyu Zou

  2. College of Electrical and Information Engineering, Beihua University, Jilin, China

    Yanlin Li & Zhenxiong Zhou

  3. Jilin Sanjiu Technology Service Co. LTD, Jilin, China

    Xu Yang

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  1. Qingyu Zou
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  2. Yanlin Li
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  3. Xu Yang
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  4. Zhenxiong Zhou
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Corresponding authors

Correspondence to Qingyu Zou, Yanlin Li or Zhenxiong Zhou.

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The authors declare no conflicts of interest.

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Qingyu Zou, Li, Y., Yang, X. et al. Identification of Key Nodes in Directed Network Based on Overlapping Community Structure. Aut. Control Comp. Sci. 55, 167–176 (2021). https://doi.org/10.3103/S0146411621020103

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  • DOI: https://doi.org/10.3103/S0146411621020103

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