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 search 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. 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).
    2. Ren, Yue & Jiang, Haijun & Hu, Cheng & Chen, Shanshan, 2024. "Synchronization of complex-valued multi-layer coupled systems by asynchronous intermittent event-triggered mechanisms," Applied Mathematics and Computation, Elsevier, vol. 477(C).
    3. 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.
    4. Shan, Yaping, 2025. "Disinformation in group chat social media network," Journal of Economic Behavior & Organization, Elsevier, vol. 231(C).
    5. 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).
    6. Bramoullé, Yann & Genicot, Garance, 2024. "Diffusion and targeting centrality," Journal of Economic Theory, Elsevier, vol. 222(C).
    7. 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).
    8. Michela Chessa, 2025. "Politics as A (Very) Complex System: A New Methodological Approach to Studying Fragmentation within a Council," GREDEG Working Papers 2025-16, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    9. Xu, Xiang & Yang, Wei & Li, Lingfei & Zhu, Xianqiang & Cui, Junying & Zhang, Zihan & Wu, Leilei, 2025. "TD-GCN: A novel fusion method for network topological and dynamical features," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    10. Li, Xianghua & Teng, Min & Jiang, Shihong & Han, Zhen & Gao, Chao & Nekorkin, Vladimir & Radeva, Petia, 2025. "A dynamic station-line centrality for identifying critical stations in bus-metro networks," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).
    11. 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).
    12. 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.
    13. Esfandiari, Shima & Fakhrahmad, Seyed Mostafa, 2025. "The collaborative role of K-Shell and PageRank for identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 658(C).
    14. 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).
    15. Yang Sun & Wei Zhao & Junjie Zhou, 2024. "Sequential Network Design," Papers 2409.14136, arXiv.org.
    16. Liu, Hang & Zou, Zhiyun & Jiang, Zehao & Chen, Yujiang & Yang, Qingmei & Gao, Jianzhi, 2024. "Method for utilizing the reserved lane capacity: Formation of the mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    17. Ilias Aarab & Thomas Gottron, 2025. "Network topology of the Euro Area interbank market," Papers 2502.15611, arXiv.org.
    18. 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).
    19. Yan Leng & Xiaowen Dong & Esteban Moro & Alex Pentland, 2024. "Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions," Information Systems Research, INFORMS, vol. 35(1), pages 318-338, March.
    20. repec:hal:pseptp:halshs-04188289 is not listed on IDEAS
    21. Stojkoski, Viktor & Lopez-Calva, Luis-Felipe & Bolch, Kimberly Blair & Fernandez,Almudena, 2024. "Development Acupuncture : The Network Structure of Multidimensional Poverty and Its Implications," Policy Research Working Paper Series 10882, The World Bank.

    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.