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Information diffusion under public crisis in BA scale-free network based on SEIR model — Taking COVID-19 as an example

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  • Zhang, Mingli
  • Qin, Simeng
  • Zhu, Xiaoxia

Abstract

In the view of the fact that online information in complex networks has an increasingly powerful impact on real society, an improved network public opinion diffusion model under public crisis is established in this paper. The model updates SEIR infectious disease model by using Mean Field Theory based on BA scale-free network, which presents scale-free characteristics as well as enhances the model accuracy and applicability. It conducts a sensitivity analysis and takes “2019-nCoV Explosion” as a sample, crawling through related 180-day microblogs, forwards, comments and likes on Weibo. The results demonstrate that the propagation is greatly influenced by propagation probability, the network structure, the initial spreader and social effects, which contributes to the understanding of network public opinion diffusion and the control of the information dissemination direction.

Suggested Citation

  • Zhang, Mingli & Qin, Simeng & Zhu, Xiaoxia, 2021. "Information diffusion under public crisis in BA scale-free network based on SEIR model — Taking COVID-19 as an example," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    • Handle: RePEc:eee:phsmap:v:571:y:2021:i:c:s0378437121001205
    DOI: 10.1016/j.physa.2021.125848
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    References listed on IDEAS

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    Cited by:

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    3. Ping Yu & Zhiping Wang & Yanan Sun & Peiwen Wang, 2022. "Risk Diffusion and Control under Uncertain Information Based on Hypernetwork," Mathematics, MDPI, vol. 10(22), pages 1-17, November.

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