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Social contagions on higher-order community networks

Author

Listed:
  • Li, Jiachen
  • Li, Wenjie
  • Gao, Feng
  • Cai, Meng
  • Zhang, Zengping
  • Liu, Xiaoyang
  • Wang, Wei

Abstract

Extensive real-world analysis has revealed that wide community structures and higher-order interactions can be captured by the higher-order community networks. However, the roles of the higher-order community networks in shaping social contagions are still lacking a systematic study of the strongly nonlinear characteristics of the dynamical system. We first propose a simplicial threshold model to describe the dynamics of social contagion on higher-order community networks and then provide a dimension-reduction approach to accurately and qualitatively describe the dynamical process. Both numerical analysis and theoretical results indicate that a hysteresis loop exists in the social contagion. The higher-order structural characteristic significantly reduces the gap between the threshold points. With the increase of higher-order interactions, the outbreak threshold in the network decreases. Furthermore, the stronger the community structure, the more it facilitates information spreading, demonstrating that enhancing community structure strength contributes to more efficient dissemination.

Suggested Citation

  • Li, Jiachen & Li, Wenjie & Gao, Feng & Cai, Meng & Zhang, Zengping & Liu, Xiaoyang & Wang, Wei, 2024. "Social contagions on higher-order community networks," Applied Mathematics and Computation, Elsevier, vol. 478(C).
    • Handle: RePEc:eee:apmaco:v:478:y:2024:i:c:s0096300324002935
    DOI: 10.1016/j.amc.2024.128832
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    References listed on IDEAS

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