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Rumor spreading model with the different attitudes towards rumors

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  • Hu, Yuhan
  • Pan, Qiuhui
  • Hou, Wenbing
  • He, Mingfeng

Abstract

Rumor spreading has a profound influence on people’s well-being and social stability. There are many factors influencing rumor spreading. In this paper, we recommended an assumption that among the common mass there are three attitudes towards rumors: to like rumor spreading, to dislike rumor spreading, and to be hesitant (or neutral) to rumor spreading. Based on such an assumption, a Susceptible–Hesitating–Affected–Resistant(SHAR) model is established, which considered individuals’ different attitudes towards rumor spreading. We also analyzed the local and global stability of rumor-free equilibrium and rumor-existence equilibrium, calculated the basic reproduction number of our model. With numerical simulations, we illustrated the effect of parameter changes on rumor spreading, analyzing the parameter sensitivity of the model. The results of the theoretical analysis and numerical simulations illustrated the conclusions of this study. People having different attitudes towards rumors may play different roles in the process of rumor spreading. It was surprising to find, in our research, that people who hesitate to spread rumors have a positive effect on the spread of rumors.

Suggested Citation

  • Hu, Yuhan & Pan, Qiuhui & Hou, Wenbing & He, Mingfeng, 2018. "Rumor spreading model with the different attitudes towards rumors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 331-344.
    • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:331-344
    DOI: 10.1016/j.physa.2018.02.096
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    References listed on IDEAS

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    7. Xia, Yang & Jiang, Haijun & Yu, Zhiyong, 2022. "Global dynamics of ILSR rumor spreading model with general nonlinear spreading rate in multi-lingual environment," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    8. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.
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    10. Jain, Lokesh, 2022. "An entropy-based method to control COVID-19 rumors in online social networks using opinion leaders," Technology in Society, Elsevier, vol. 70(C).
    11. Lu, Peng & Deng, Liping & Liao, Hongbing, 2019. "Conditional effects of individual judgment heterogeneity in information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 335-344.
    12. Nwaibeh, E.A. & Chikwendu, C.R., 2023. "A deterministic model of the spread of scam rumor and its numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 111-129.
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    14. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "Individuals with the firm heart are conducive to cooperation in social dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    15. Liang’an Huo & Yuqing Zhang, 2022. "Effect of Global and Local Refutation Mechanism on Rumor Propagation in Heterogeneous Network," Mathematics, MDPI, vol. 10(4), pages 1-17, February.
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    19. Zhonggen Sun & Xin Cheng & Ruilian Zhang & Bingqing Yang, 2020. "Factors Influencing Rumour Re-Spreading in a Public Health Crisis by the Middle-Aged and Elderly Populations," IJERPH, MDPI, vol. 17(18), pages 1-14, September.

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