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An evolutionary game for the diffusion of rumor in complex networks

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  • Li, Dandan
  • Ma, Jing
  • Tian, Zihao
  • Zhu, Hengmin

Abstract

In this paper, we investigate the rumor diffusion process according to the evolutionary game framework. By using three real social network datasets, we find that increasing the judgment ability of individuals could curb the diffusion of rumor effectively. Under the same level of punishment cost, there are more spreaders in the network that has larger average degree. Moreover, the punishment fraction has more significant impact than the risk coefficient on the controlling of rumor diffusion. There exist some optimal risk coefficients and punishment fractions that could help more people refusing to spread rumor. In addition, the effect of the tie strength on the final fraction of spreaders is investigated. The results indicate that the rumor can be suppressed soon if the individuals preferentially select the neighbor either weaker or stronger ties persistently to update their strategy. However, choosing neighbor blindly may promote the spread of rumor. Finally, by comparing three kinds of punishment mechanisms, we show that taking the lead in punishing the higher degree nodes is the most effective measure to reduce the coverage of rumor.

Suggested Citation

  • Li, Dandan & Ma, Jing & Tian, Zihao & Zhu, Hengmin, 2015. "An evolutionary game for the diffusion of rumor in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 51-58.
    • Handle: RePEc:eee:phsmap:v:433:y:2015:i:c:p:51-58
    DOI: 10.1016/j.physa.2015.03.080
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    21. Li, Ya & Chen, Shanxiong & Niu, Ben, 2018. "Reward depending on public funds stimulates cooperation in spatial prisoner’s dilemma games," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 38-45.

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