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ORIGINAL RESEARCH article

Front. Phys.
Sec. Social Physics
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1529904

Identifying Vital Spreaders in Large-Scale Networks Based on Neighbor Multilayer Contributions

Provisionally accepted
Weiwei Zhu Weiwei Zhu 1*Xuchen Meng Xuchen Meng 2Jiaye Sheng Jiaye Sheng 2*Dayong Zhang Dayong Zhang 2
  • 1 University of Chinese Academy of Sciences, Beijing, Beijing, China
  • 2 Harbin Institute of Technology, Harbin, China

The final, formatted version of the article will be published soon.

    Identifying influential spreaders is an important issue in complex networks and plays an essential role in information propagation and disease immunity. Identifying the spreading ability of a node from its neighbor information has become a common method. However, the existing methods lack specific explanations for the role of neighbors and cannot distinguish their contributions to information spread. Therefore, we propose an efficient ranking algorithm based on strictly distinguishing the contribution of neighbors in information spreading. The algorithm’s ranking is produced by combining the number of common neighbors and the K-shell value of each node. Extensive experiments conducted with Kendall’s rank correlation, monotonicity, and SIR epidemic model on real-world networks demonstrate the effectiveness of our algorithm. Furthermore, computational complexity analysis indicates that our algorithm has the lower cost of time consumption and can be applicable to large-scale networks.

    Keywords: large-scale network, rankinig method, vital spreaders, Common neighbors, SIR epidemic model

    Received: 18 Nov 2024; Accepted: 06 Jan 2025.

    Copyright: © 2025 Zhu, Meng, Sheng and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Weiwei Zhu, University of Chinese Academy of Sciences, Beijing, 10049, Beijing, China
    Jiaye Sheng, Harbin Institute of Technology, Harbin, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.