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Dynamical Behaviors of Rumor Spreading Model with Control Measures

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  • Xia-Xia Zhao
  • Jian-Zhong Wang

Abstract

Rumor has no basis in fact and flies around. And in general, it is propagated for a certain motivation, either for business, economy, or pleasure. It is found that the web does expose us to more rumor and increase the speed of the rumors spread. Corresponding to these new ways of spreading, the government should carry out some measures, such as issuing message by media, punishing the principal spreader, and enhancing management of the internet. In order to assess these measures, dynamical models without and with control measures are established. Firstly, for two models, equilibria and the basic reproduction number of models are discussed. More importantly, numerical simulation is implemented to assess control measures of rumor spread between individuals‐to‐individuals and medium‐to‐individuals. Finally, it is found that the amount of message released by government has the greatest influence on the rumor spread. The reliability of government and the cognizance ability of the public are more important. Besides that, monitoring the internet to prevent the spread of rumor is more important than deleting messages in media which already existed. Moreover, when the minority of people are punished, the control effect is obvious.

Suggested Citation

  • Xia-Xia Zhao & Jian-Zhong Wang, 2014. "Dynamical Behaviors of Rumor Spreading Model with Control Measures," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:247359
    DOI: 10.1155/2014/247359
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    References listed on IDEAS

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    1. Zan, Yongli & Wu, Jianliang & Li, Ping & Yu, Qinglin, 2014. "SICR rumor spreading model in complex networks: Counterattack and self-resistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 159-170.
    2. Lebensztayn, E. & Rodriguez, P.M., 2013. "A connection between a system of random walks and rumor transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5793-5800.
    3. Xia-Xia Zhao & Jian-Zhong Wang, 2014. "Dynamics of an Information Spreading Model with Isolation," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    4. Liang'an Huo & Tingting Lin & Peiqing Huang, 2013. "Dynamical Behavior of a Rumor Transmission Model with Psychological Effect in Emergency Event," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-9, December.
    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. Liang′an Huo & Tingting Lin & Peiqing Huang, 2013. "Dynamical Behavior of a Rumor Transmission Model with Psychological Effect in Emergency Event," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    7. Li, Weihua & Tang, Shaoting & Pei, Sen & Yan, Shu & Jiang, Shijin & Teng, Xian & Zheng, Zhiming, 2014. "The rumor diffusion process with emerging independent spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 121-128.
    8. 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.
    9. Zhao, Laijun & Cui, Hongxin & Qiu, Xiaoyan & Wang, Xiaoli & Wang, Jiajia, 2013. "SIR rumor spreading model in the new media age," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 995-1003.
    10. Zhao, Laijun & Wang, Jiajia & Chen, Yucheng & Wang, Qin & Cheng, Jingjing & Cui, Hongxin, 2012. "SIHR rumor spreading model in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2444-2453.
    11. Xia-Xia Zhao & Jian-Zhong Wang, 2014. "Dynamics of an Information Spreading Model with Isolation," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-6, April.
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    Cited by:

    1. Yuan Xu & Renjie Mei & Yujie Yang & Zhengmin Kong, 2019. "Modeling and Analysis of Rumor Spreading with Social Reinforcement Mechanism," Advances in Mathematical Physics, John Wiley & Sons, vol. 2019(1).
    2. Polin, Sujana Azmi & Hasan, Md. Nahid & Islam, Saiful & Podder, Chandra Nath, 2025. "Behavioral influences on rumor dynamics: A compartmental model with hesitation, forgetting, and self-remembering mechanisms in complex heterogeneous social networks," Chaos, Solitons & Fractals, Elsevier, vol. 201(P3).

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