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Influence maximization in hypergraphs: A self-optimizing algorithm based on electrostatic field

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  • Li, Shuyu
  • Li, Xiang

Abstract

Multi-individual interactions are ubiquitous in the real world, which are usually modeled by hypergraphs. Similar to low-order networks, there are special key nodes in high-order networks that are highly influential and play a crucial role in information dissemination. The objective of the influence maximization problem is to find an optimal set of nodes that maximizes the influence of the network, while maximizing influence in hypergraphs has been neglected so far, and how to explore higher-order interactions from multiple perspectives and exploit the features of higher-order structures are still open questions. To solve the above problems, a self-optimization algorithm based on electrostatic field is proposed. The network is innovatively viewed as an electrostatic field to uncover the interaction forces of the nodes in it. The improved localized Physarum polycephalum algorithm is used to assign values to the initial charges of the nodes. The effective distance among hyperedges and nodes is redefined. Furthermore, the self-optimizing update algorithm is designed to reduce the overlap of nodes’ influence ranges in the optimal set. Percolation, SIR, Top-k, and correlation experiments are conducted on eight real-world networks, and the superiority of our proposed algorithm in this paper is verified by comparing with six algorithms.

Suggested Citation

  • Li, Shuyu & Li, Xiang, 2023. "Influence maximization in hypergraphs: A self-optimizing algorithm based on electrostatic field," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
  • Handle: RePEc:eee:chsofr:v:174:y:2023:i:c:s0960077923007890
    DOI: 10.1016/j.chaos.2023.113888
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    References listed on IDEAS

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    1. Liu, Panfeng & Li, Longjie & Fang, Shiyu & Yao, Yukai, 2021. "Identifying influential nodes in social networks: A voting approach," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    2. L. V. Gambuzza & F. Patti & L. Gallo & S. Lepri & M. Romance & R. Criado & M. Frasca & V. Latora & S. Boccaletti, 2021. "Stability of synchronization in simplicial complexes," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    3. Gideon Rosenthal & František Váša & Alessandra Griffa & Patric Hagmann & Enrico Amico & Joaquín Goñi & Galia Avidan & Olaf Sporns, 2018. "Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    4. Yuanzhao Zhang & Maxime Lucas & Federico Battiston, 2023. "Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    5. Serrano, Daniel Hernández & Villarroel, Javier & Hernández-Serrano, Juan & Tocino, Ángel, 2023. "Stochastic simplicial contagion model," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    6. Tocchi, Daniela & Sys, Christa & Papola, Andrea & Tinessa, Fiore & Simonelli, Fulvio & Marzano, Vittorio, 2022. "Hypergraph-based centrality metrics for maritime container service networks: A worldwide application," Journal of Transport Geography, Elsevier, vol. 98(C).
    7. Wang, Yan & Li, Haozhan & Zhang, Ling & Zhao, Linlin & Li, Wanlan, 2022. "Identifying influential nodes in social networks: Centripetal centrality and seed exclusion approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    8. Unai Alvarez-Rodriguez & Federico Battiston & Guilherme Ferraz Arruda & Yamir Moreno & Matjaž Perc & Vito Latora, 2021. "Evolutionary dynamics of higher-order interactions in social networks," Nature Human Behaviour, Nature, vol. 5(5), pages 586-595, May.
    9. Jian-Wei Wang & Li-Li Rong & Qiu-Hong Deng & Ji-Yong Zhang, 2010. "Evolving hypernetwork model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 493-498, October.
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