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Energy model for rumor propagation on social networks

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  • Han, Shuo
  • Zhuang, Fuzhen
  • He, Qing
  • Shi, Zhongzhi
  • Ao, Xiang

Abstract

With the development of social networks, the impact of rumor propagation on human lives is more and more significant. Due to the change of propagation mode, traditional rumor propagation models designed for word-of-mouth process may not be suitable for describing the rumor spreading on social networks. To overcome this shortcoming, we carefully analyze the mechanisms of rumor propagation and the topological properties of large-scale social networks, then propose a novel model based on the physical theory. In this model, heat energy calculation formula and Metropolis rule are introduced to formalize this problem and the amount of heat energy is used to measure a rumor’s impact on a network. Finally, we conduct track experiments to show the evolution of rumor propagation, make comparison experiments to contrast the proposed model with the traditional models, and perform simulation experiments to study the dynamics of rumor spreading. The experiments show that (1) the rumor propagation simulated by our model goes through three stages: rapid growth, fluctuant persistence and slow decline; (2) individuals could spread a rumor repeatedly, which leads to the rumor’s resurgence; (3) rumor propagation is greatly influenced by a rumor’s attraction, the initial rumormonger and the sending probability.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:394:y:2014:i:c:p:99-109
    DOI: 10.1016/j.physa.2013.10.003
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    References listed on IDEAS

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    15. Ketelaar, Paul E. & Janssen, Loes & Vergeer, Maurice & van Reijmersdal, Eva A. & Crutzen, Rik & van ‘t Riet, Jonathan, 2016. "The success of viral ads: Social and attitudinal predictors of consumer pass-on behavior on social network sites," Journal of Business Research, Elsevier, vol. 69(7), pages 2603-2613.
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    19. Alzahrani, Ahmed Ibrahim & Sarsam, Samer Muthana & Al-Samarraie, Hosam & Alblehai, Fahad, 2023. "Exploring the sentimental features of rumor messages and investors' intentions to invest," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 433-444.
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    21. Wang, Chenxu & Wang, Gaoshuai & Luo, Xiapu & Li, Hui, 2019. "Modeling rumor propagation and mitigation across multiple social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    22. Geng, Lixiao & Zheng, Hongye & Qiao, Gaigai & Geng, Lisha & Wang, Ke, 2023. "Online public opinion dissemination model and simulation under media intervention from different perspectives," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
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    25. 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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