4.6 Article

Rumor and authoritative information propagation model considering super spreading in complex social networks

期刊

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.physa.2018.04.082

关键词

Rumor and authoritative information propagation; Super spreading; Complex social networks; Basic reproduction number

资金

  1. National Natural Science Foundation of China [71271186, 71671159]
  2. Natural Science Foundation of Hebei [G2016203220, G2017203319]
  3. Research Project of Humanities and Social Sciences of Ministry of Education of China [17YJCZH109]
  4. Innovation research assistant support project of Yanshan University [CXZS201710]

向作者/读者索取更多资源

The research of rumor spreading and controlling has become an important issue in social networks. In this paper, we propose a novel rumor and authoritative information propagation model considering the super spreading mechanism. We derive mean-field equations to describe the dynamics of the rumor and authoritative information propagation model. Then the basic reproduction number and the final size of rumor and authoritative information are estimated. Simulations are conducted in a Barabasi-Albert scale-free network to verify the effectiveness by comparing the proposed model with real data in Sina Weibo and to analyze the dynamics of the model. The results show that the influence of super spreading mechanism on rumor is greater than that on authoritative information. The presence of the super spreading mechanism only on rumor will cause explosive growth of the final rumor spreading size. Besides, the stronger the force of authoritative information, the smaller the final rumor spreading size and the larger the final authoritative information size. What is more, the influence of the force of authoritative information to attract individuals to spread it has greater influence on the final rumor and authoritative information spreading size than the force to forbid spreading rumors. The results are useful to understand better the mechanism of rumor propagation and refutation in complex social networks. (C) 2018 Elsevier B.V. All rights reserved.

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