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An interplay model for authorities’ actions and rumor spreading in emergency event

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  • Huo, Liang-an
  • Huang, Peiqing
  • Fang, Xing

Abstract

Rumor spreading influences how rational individuals assess risks and evaluate needs, especially, it affects authorities to make decisions in an emergency-affected environments. Conversely, authorities’ response to emergency will induct public opinions as well. In this paper, we present a simple model to describe the interplay between rumor spreading and authorities’ actions in emergency situation based on utility theory. By drawing from differential equations we found that it is possible to minimize negative social utility of rumor spreading in the control of situation. At the same time, authorities’ proactive actions can improve rumor management in emergency situation and yield positive social utility. Finally, we outline strategies for authorities that can contribute to rumor management in an emergency event.

Suggested Citation

  • Huo, Liang-an & Huang, Peiqing & Fang, Xing, 2011. "An interplay model for authorities’ actions and rumor spreading in emergency event," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3267-3274.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:20:p:3267-3274
    DOI: 10.1016/j.physa.2011.05.008
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    References listed on IDEAS

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    1. Kosfeld, Michael, 2005. "Rumours and markets," Journal of Mathematical Economics, Elsevier, vol. 41(6), pages 646-664, September.
    2. Buzna, Lubos & Peters, Karsten & Helbing, Dirk, 2006. "Modelling the dynamics of disaster spreading in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 132-140.
    3. Nekovee, M. & Moreno, Y. & Bianconi, G. & Marsili, M., 2007. "Theory of rumour spreading in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 457-470.
    4. Zhang, Zi-li & Zhang, Zi-qiong, 2009. "An interplay model for rumour spreading and emergency development," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4159-4166.
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    Citations

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    Cited by:

    1. Wang, Chuanbiao & Liu, Ruiying & Wang, Yan, 2023. "The spread dynamics model of the interaction between rumors and derivative rumors in emergencies under the control strategy," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    2. Li, Dandan & Ma, Jing, 2017. "How the government’s punishment and individual’s sensitivity affect the rumor spreading in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 284-292.
    3. Zhao, Laijun & Wang, Qin & Cheng, Jingjing & Zhang, Ding & Ma, Ting & Chen, Yucheng & Wang, Jiajia, 2012. "The impact of authorities’ media and rumor dissemination on the evolution of emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3978-3987.
    4. Zhang, Yi & Xu, Jiuping & Nekovee, Maziar & Li, Zongmin, 2022. "The impact of official rumor-refutation information on the dynamics of rumor spread," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Han, Shuo & Zhuang, Fuzhen & He, Qing & Shi, Zhongzhi & Ao, Xiang, 2014. "Energy model for rumor propagation on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 99-109.
    6. 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.
    7. Yao Lu & Zheng Ji & Xiaoqi Zhang & Yanqiao Zheng & Han Liang, 2020. "Re-Thinking the Role of Government Information Intervention in the COVID-19 Pandemic: An Agent-Based Modeling Analysis," IJERPH, MDPI, vol. 18(1), pages 1-17, December.
    8. Lu, Peng & Yao, Qi & Lu, Pengfei, 2019. "Two-stage predictions of evolutionary dynamics during the rumor dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 349-369.
    9. Hainan Huang & Weifan Chen & Tian Xie & Yaoyao Wei & Ziqing Feng & Weijiong Wu, 2021. "The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment Based on System Dynamics and Cross-Validation," IJERPH, MDPI, vol. 18(8), pages 1-25, April.
    10. 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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