IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v192y2025ics0960077925000311.html
   My bibliography  Save this article

Efficient hybrid PageRank centrality computation for multilayer networks

Author

Listed:
  • Shen, Zhao-Li
  • Jiao, Yue-Hao
  • Wei, Yi-Kun
  • Wen, Chun
  • Carpentieri, Bruno

Abstract

Quantifying node centrality in multilayer networks is crucial for identifying influential nodes across various applications. Building on the PageRank model for single-layer networks, Lv et al. recently introduced a promising multilayer PageRank model for assessing node and layer centrality. In this paper, we reformulate this model within a discrete Markov chain framework. Our approach incorporates link diversity to enhance centrality measurement and ensures irreducibility within the internal Markov chains. This refinement enables an efficient computational strategy leveraging numerical algebra techniques. Experiments across diverse multilayer networks demonstrate the model’s effectiveness and computational efficiency, particularly for large-scale networks.

Suggested Citation

  • Shen, Zhao-Li & Jiao, Yue-Hao & Wei, Yi-Kun & Wen, Chun & Carpentieri, Bruno, 2025. "Efficient hybrid PageRank centrality computation for multilayer networks," Chaos, Solitons & Fractals, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:chsofr:v:192:y:2025:i:c:s0960077925000311
    DOI: 10.1016/j.chaos.2025.116018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077925000311
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2025.116018?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Francis Bloch & Matthew O. Jackson & Pietro Tebaldi, 2023. "Centrality measures in networks," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 61(2), pages 413-453, August.
    2. Ma, Jinlong & Kong, Lingkang, 2023. "The influence of edge-adding strategy on traffic capacity of multilayer network," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    3. Beheshtian-Ardakani, Arash & Salehi, Mostafa & Sharma, Rajesh, 2023. "CMPN: Modeling and analysis of soccer teams using Complex Multiplex Passing Network," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    4. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    5. Jo Cheriyan & G. P. Sajeev, 2020. "m-PageRank: A NOVEL CENTRALITY MEASURE FOR MULTILAYER NETWORKS," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(05), pages 1-20, August.
    6. Yang, Pingle & Meng, Fanyuan & Zhao, Laijun & Zhou, Lixin, 2023. "AOGC: An improved gravity centrality based on an adaptive truncation radius and omni-channel paths for identifying key nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alex S. O. Toledo & Laura C. Carpi & Allbens P. F. Atman & A. P. Baêta Scarpelli, 2025. "Outlier mining in criminal networks: the role of machine learning and outlier detection models," Journal of Computational Social Science, Springer, vol. 8(2), pages 1-22, May.
    2. Shan, Yaping, 2025. "Disinformation in group chat social media network," Journal of Economic Behavior & Organization, Elsevier, vol. 231(C).
    3. Zhao, Zhili & Liu, Xupeng & Sun, Yue & Zhang, Nana & Hu, Ahui & Wang, Shiling & Tu, Yingyuan, 2025. "Influence maximization based on bottom-up community merging," Chaos, Solitons & Fractals, Elsevier, vol. 193(C).
    4. Bramoullé, Yann & Genicot, Garance, 2024. "Diffusion and targeting centrality," Journal of Economic Theory, Elsevier, vol. 222(C).
    5. Song, Honglin & Li, Yutao & Pan, Pengyu & Yuan, Bo & Liu, Tianbiao, 2025. "Multilayer network framework and metrics for table tennis analysis: Integrating network science, entropy, and machine learning," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    6. Gao, Shanshan & Zhang, Shenggui & Chen, Xinzhuang, 2023. "Effects of changing the weights of arcs on the consensus convergence rate of a leader–follower multi-agent system," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    7. van den Brink, René & Rusinowska, Agnieszka, 2024. "Degree centrality, von Neumann–Morgenstern expected utility and externalities in networks," European Journal of Operational Research, Elsevier, vol. 319(2), pages 669-677.
    8. Xu, Guiqiong & Meng, Lei, 2023. "A novel algorithm for identifying influential nodes in complex networks based on local propagation probability model," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    9. Shen, Jingwei & Zong, Huiming, 2023. "Identification of critical transportation cities in the multimodal transportation network of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    10. López, Susana & Molina, Elisenda & Saboyá, Martha & Tejada, Juan, 2024. "Node centrality based on its edges importance: The Position centrality," Mathematical Social Sciences, Elsevier, vol. 132(C), pages 90-104.
    11. Zhang, Hui & Cui, Yu, 2024. "Understanding multimodal travel mobilities of dockless bike-sharing and metro: A multilayer network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    12. Gibbs, Michael & Mengel, Friederike & Siemroth, Christoph, 2025. "Innovator Networks Within the Firm and the Quality of Innovation," IZA Discussion Papers 17966, Institute of Labor Economics (IZA).
    13. Ke, Xingfu & Wen, Youjin & Yu, Hao & Meng, Fanyuan, 2024. "A simple model of global cascades in signed networks," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    14. Della Lena, Sebastiano, 2024. "The spread of misinformation in networks with individual and social learning," European Economic Review, Elsevier, vol. 168(C).
    15. Ding, Fangyi & Tang, Yan & Wang, Yamin & Zhao, Zhan, 2025. "Unraveling the network effects in station ridership growth patterns under metro network expansion," Journal of Transport Geography, Elsevier, vol. 125(C).
    16. Meng, Lei & Xu, Guiqiong & Dong, Chen, 2025. "An improved gravity model for identifying influential nodes in complex networks considering asymmetric attraction effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 657(C).
    17. Nicolas Verbeek, 2024. "‘Wolf Warriors’ in the UN Security Council? Investigating power shifts through blaming," Global Policy, London School of Economics and Political Science, vol. 15(S2), pages 38-50, May.
    18. Dong, Qian & Yuan, Wenying & Tong, Tianchi & Sun, Jinsheng, 2024. "The distributed fault diagnosis for nonlinear complex dynamical networks based on σ-detection criterion," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    19. Zhou, Lili & Zhang, Yuhao & Tan, Fei & Huang, Mingzhe, 2023. "Adaptive secure synchronization of complex networks under mixed attacks via time-controllable technology," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    20. Wang, Peng & Ling, Guang & Zhao, Pei & Pan, Wenqiu & Ge, Ming-Feng, 2024. "Identification of important nodes in multi-layer hypergraphs based on fuzzy gravity model and node centrality distribution characteristics," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:192:y:2025:i:c:s0960077925000311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.