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Identifying node importance in complex networks

Author

Listed:
  • Hu, Ping
  • Fan, Wenli
  • Mei, Shengwei

Abstract

In this paper, we propose a novel node importance evaluation method from the perspective of the existence of mutual dependence among nodes. The node importance comprises its initial importance and the importance contributions from both the adjacent and non-adjacent nodes according to the dependence strength between them. From the simulation analyses on an example network and the ARPA network, we observe that our method can well identify the node importance. Then, the cascading failures on the Netscience and E-mail networks demonstrate that the networks are more vulnerable when continuously removing the important nodes identified by our method, which further proves the accuracy of our method.

Suggested Citation

  • Hu, Ping & Fan, Wenli & Mei, Shengwei, 2015. "Identifying node importance in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 169-176.
    • Handle: RePEc:eee:phsmap:v:429:y:2015:i:c:p:169-176
    DOI: 10.1016/j.physa.2015.02.002
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    Citations

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    Cited by:

    1. Wen, Xiangxi & Tu, Congliang & Wu, Minggong, 2018. "Node importance evaluation in aviation network based on “No Return” node deletion method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 546-559.
    2. Hu, Ping & Fan, Wen-Li, 2020. "Mitigation strategy against cascading failures considering vulnerable transmission line in power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    3. Zhu, Canshi & Wang, Xiaoyang & Zhu, Lin, 2017. "A novel method of evaluating key nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 43-50.
    4. Wang, Ning & Gao, Ying & He, Jia-tao & Yang, Jun, 2022. "Robustness evaluation of the air cargo network considering node importance and attack cost," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. Dong, Lijun & Wang, Yi & Liu, Ran & Pi, Benjie & Wu, Liuyi, 2016. "Toward edge minability for role mining in bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 274-286.
    6. 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.
    7. Liu, Wei & Song, Zhaoyang, 2020. "Review of studies on the resilience of urban critical infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Huang, Wencheng & Li, Haoran & Yin, Yanhui & Zhang, Zhi & Xie, Anhao & Zhang, Yin & Cheng, Guo, 2024. "Node importance identification of unweighted urban rail transit network: An Adjacency Information Entropy based approach," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    9. Zhou, Jin & Xu, Weixiang & Guo, Xin & Liu, Xumin, 2017. "A hierarchical network modeling method for railway tunnels safety assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 226-239.
    10. Col, Alcebiades Dal & Petronetto, Fabiano, 2023. "Graph regularization centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).

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