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A novel method to evaluate node importance in complex networks

Author

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  • Yang, Yuanzhi
  • Yu, Lei
  • Wang, Xing
  • Zhou, Zhongliang
  • Chen, You
  • Kou, Tian

Abstract

The measurement of node importance in complex networks has an important impact on the stability and robustness of networks, such as stopping the spread of disease and rumors and preventing power grids from being powered off. A variety of network centricity criteria are used to evaluate the importance of nodes, while each of them accompanied by a single criterion has its own shortcomings and limitations. A novel method is therefore proposed to rank node importance based on combining the existing centrality criteria. This paper considers degree centrality, closeness centrality, and betweenness centrality and raises an integrated measuring method to evaluate node importance in complex networks. In our method, the weight of each criterion is calculated by entropy weighting method which overcomes the impact of the subjective factor, and the Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is used for ranking nodes’ importance. Finally, four experiments are conducted based on four actual networks to verify the feasibility and effectiveness of the proposed method. The experimental results demonstrate that the performance of ranking node importance of the proposed method is better than a single centrality criterion.

Suggested Citation

  • Yang, Yuanzhi & Yu, Lei & Wang, Xing & Zhou, Zhongliang & Chen, You & Kou, Tian, 2019. "A novel method to evaluate node importance in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119306740
    DOI: 10.1016/j.physa.2019.121118
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    Citations

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    Cited by:

    1. Wang, Chenlan & Wang, Nachuan & Zhang, Xiaotian, 2021. "Network performance measure and importance identification: A case study of private car in Zhengzhou city," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    2. Zhou, Yaoming & Kundu, Tanmoy & Goh, Mark & Sheu, Jiuh-Biing, 2023. "Beyond throughput: Incorporating air transport network topology in airport performance measurement," Journal of Air Transport Management, Elsevier, vol. 112(C).
    3. 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).
    4. Dong, Chen & Xu, Guiqiong & Meng, Lei & Yang, Pingle, 2022. "CPR-TOPSIS: A novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    5. Wu, Gongyu & Li, Meiyan & Li, Zhaojun Steven, 2021. "A Gene Importance based Evolutionary Algorithm (GIEA) for identifying critical nodes in Cyber–Physical Power Systems," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    6. Al-Azim, Nouran Ayman R. Abd & Gharib, Tarek F. & Afify, Yasmine & Hamdy, Mohamed, 2020. "Influence propagation: Interest groups and node ranking models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    7. Wang, Shuliang & Sun, Jingya & Zhang, Jianhua & Dong, Qiqi & Gu, Xifeng & Chen, Chen, 2023. "Attack-Defense game analysis of critical infrastructure network based on Cournot model with fixed operating nodes," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    8. Zhou, Yuyang & Zheng, Shuyan & Hu, Zhonghui & Chen, Yanyan, 2022. "Metro station risk classification based on smart card data: A case study in Beijing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    9. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Exploring node importance evolution of weighted complex networks in urban rail transit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    10. Fu, Xin & Qiang, Yongjie & Liu, Xuxu & Jiang, Ying & Cui, Zhiwei & Zhang, Deyu & Wang, Jianwei, 2022. "Will multi-industry supply chains' resilience under the impact of COVID-19 pandemic be different? A perspective from China's highway freight transport," Transport Policy, Elsevier, vol. 118(C), pages 165-178.

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