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Ranking influential nodes in complex networks with structural holes

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  • Hu, Ping
  • Mei, Ting

Abstract

Ranking influential nodes in complex networks is of great theoretical and practical significance to ensure the safe operations of networks. In view of the important role structural hole nodes usually play in information spreading in complex networks, we propose a novel ranking method of influential nodes using structural holes called E-Burt method, which can be applied to weighted networks. This method fully takes into account the total connectivity strengths of the node in its local scope, the number of the connecting edges and the distributions of the total connectivity strengths on its connecting edges. The simulation results on the susceptible–infectious–recovered (SIR) dynamics suggest that the proposed E-Burt method can rank influential nodes more effectively and accurately in complex networks.

Suggested Citation

  • Hu, Ping & Mei, Ting, 2018. "Ranking influential nodes in complex networks with structural holes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 624-631.
    • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:624-631
    DOI: 10.1016/j.physa.2017.08.049
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    References listed on IDEAS

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    Cited by:

    1. Sun, Hong-liang & Chen, Duan-bing & He, Jia-lin & Ch’ng, Eugene, 2019. "A voting approach to uncover multiple influential spreaders on weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 303-312.
    2. Zhang, Qiang & Pu, Shunhao & Luo, Lihua & Liu, Zhichao & Xu, Jie, 2022. "Revisiting important ports in container shipping networks: A structural hole-based approach," Transport Policy, Elsevier, vol. 126(C), pages 239-248.
    3. Ma, Fei & Wang, Ping & Yao, Bing, 2021. "Random walks on Fibonacci treelike models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).

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