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Rumor-Propagation Model with Consideration of Refutation Mechanism in Homogeneous Social Networks

Author

Listed:
  • Laijun Zhao
  • Xiaoli Wang
  • Jiajia Wang
  • Xiaoyan Qiu
  • Wanlin Xie

Abstract

In recent years, increasing attention has been paid to how to effectively manage rumor propagation. Based on previous studies of rumor propagation and some strategies used by the authorities to refute rumors and manage rumor propagation, we develop a new rumor-propagation model with consideration of refutation mechanism. In this paper, we describe the dynamic process of rumor propagation by accounting for the refutation mechanism in homogeneous social networks. And then, we derive mean-field equations for rumor-propagation process. We then analyze the stability of the model with respect to changes in parameter values. Our results show that there exists a critical threshold that is inversely proportional to the average degree of the social networks and is positively correlated with the strength of the refutation mechanism. If the spreading rate is bigger than the critical threshold , rumors can be spread. Our numerical simulations in homogeneous networks demonstrate that increasing the ignorant’s refutation rate can reduce the peak value of spreaders density, which is better than increasing the spreader’s refutation rate . Therefore, based on the seriousness of the rumor propagation and the rumor-propagation rate, the authorities can choose effective strategies that increase the refutation rate so that they can reduce the maximum influence of the rumor.

Suggested Citation

  • Laijun Zhao & Xiaoli Wang & Jiajia Wang & Xiaoyan Qiu & Wanlin Xie, 2014. "Rumor-Propagation Model with Consideration of Refutation Mechanism in Homogeneous Social Networks," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-11, August.
  • Handle: RePEc:hin:jnddns:659273
    DOI: 10.1155/2014/659273
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    Cited by:

    1. Dayan, Fazal & Rafiq, Muhammad & Ahmed, Nauman & Baleanu, Dumitru & Raza, Ali & Ahmad, Muhammad Ozair & Iqbal, Muhammad, 2022. "Design and numerical analysis of fuzzy nonstandard computational methods for the solution of rumor based fuzzy epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    2. Jianhong Chen & Hongcai Ma & Shan Yang, 2023. "SEIOR Rumor Propagation Model Considering Hesitating Mechanism and Different Rumor-Refuting Ways in Complex Networks," Mathematics, MDPI, vol. 11(2), pages 1-22, January.
    3. 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.
    4. Yin, Fulian & Pang, Hongyu & Xia, Xinyu & Shao, Xueying & Wu, Jianhong, 2021. "COVID-19 information contact and participation analysis and dynamic prediction in the Chinese Sina-microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    5. Sahafizadeh, Ebrahim & Tork Ladani, Behrouz, 2023. "Soft rumor control in mobile instant messengers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    6. Wang, Chaoqian, 2020. "Dynamics of conflicting opinions considering rationality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).

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