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Impact of dual media on misinformation spread in heterogeneous online social networks

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  • Zhai, Shidong
  • Wang, Xin
  • Zhu, Wei
  • Chen, Guanrong

Abstract

The rapid spread of misinformation through online social networks presents a significant threat to social stability, especially during public crises. This study develops a Susceptible–Asymptomatic–Infected–Recovered (SAIR) model for misinformation spread. It incorporates dual media coverage and network heterogeneity, and addresses key limitations of existing models that assume network degree-homogeneity and oversimplify media effects. The model includes both positive media reports (fact-checking) represented by saturation functions and the amplification of negative media within degree-heterogeneous networks. Using mean-field theory and next-generation matrix methods, the basic reproduction number is derived and the stability and existence conditions of both misinformation-free and misinformation-endemic equilibria are established. Numerical simulations show that positive media reports reduce the peak and final scale of misinformation by 11% and 18%, respectively, while hub nodes accelerate early-stage misinformation spread. Sensitivity analysis identifies critical factors influencing misinformation dynamics, highlighting the importance of targeted interventions on high-degree nodes. These results offer valuable insights for policymakers to design intervention strategies that leverage media polarity regulation and mitigate network vulnerabilities.

Suggested Citation

  • Zhai, Shidong & Wang, Xin & Zhu, Wei & Chen, Guanrong, 2025. "Impact of dual media on misinformation spread in heterogeneous online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 680(C).
    • Handle: RePEc:eee:phsmap:v:680:y:2025:i:c:s0378437125006764
    DOI: 10.1016/j.physa.2025.131024
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    References listed on IDEAS

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