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Rumor spreading in online social networks by considering the bipolar social reinforcement

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

Abstract

Considering the bipolar social reinforcement which includes positive and negative effects, in this paper we explore the rumor spreading dynamics in online social networks. By means of the generation function and cavity method developed from statistical physics of disordered system, the rumor spreading threshold can be theoretically drawn. Simulation results indicate that decreasing the positive reinforcement factor or increasing the negative reinforcement factor can suppress the rumor spreading effectively. By analyzing the topological properties of the real world social network, we find that the nodes with lower degree usually have smaller weight. However, the nodes with lower degree may have larger k-shell. In order to curb rumor spreading, some control strategies that are based on the nodes’ degree, k-shell and weight are presented. By comparison, we show that controlling those nodes that have larger degree or weight are two effective strategies to prevent the rumor spreading.

Suggested Citation

  • Ma, Jing & Li, Dandan & Tian, Zihao, 2016. "Rumor spreading in online social networks by considering the bipolar social reinforcement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 108-115.
    • Handle: RePEc:eee:phsmap:v:447:y:2016:i:c:p:108-115
    DOI: 10.1016/j.physa.2015.12.005
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    Cited by:

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    2. Li, Dandan & Ma, Jing, 2017. "How the government’s punishment and individual’s sensitivity affect the rumor spreading in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 284-292.
    3. Hosni, Adil Imad Eddine & Li, Kan & Ahmad, Sadique, 2020. "Analysis of the impact of online social networks addiction on the propagation of rumors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    4. Tian, Yong & Ding, Xuejun, 2019. "Rumor spreading model with considering debunking behavior in emergencies," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    5. Lu, Peng & Deng, Liping & Liao, Hongbing, 2019. "Conditional effects of individual judgment heterogeneity in information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 335-344.
    6. Chen Jianhong & Song Qinghua & Zhou Zhiyong, 2017. "Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism," Journal of Systems Science and Information, De Gruyter, vol. 5(6), pages 571-584, December.
    7. Huo, Liang’an & Wang, Li & Song, Guoxiang, 2017. "Global stability of a two-mediums rumor spreading model with media coverage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 757-771.
    8. Chen, Guanghua, 2019. "ILSCR rumor spreading model to discuss the control of rumor spreading in emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 88-97.
    9. Jia, Pingqi & Wang, Chao & Zhang, Gaoyu & Ma, Jianfeng, 2019. "A rumor spreading model based on two propagation channels in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 342-353.
    10. Ma, Jing & Zhu, He, 2018. "Rumor diffusion in heterogeneous networks by considering the individuals’ subjective judgment and diverse characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 276-287.
    11. Linhe Zhu & Hongyong Zhao, 2017. "Dynamical behaviours and control measures of rumour-spreading model with consideration of network topology," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(10), pages 2064-2078, July.
    12. Lu, Peng & Yao, Qi & Lu, Pengfei, 2019. "Two-stage predictions of evolutionary dynamics during the rumor dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 349-369.
    13. Fei Wang & Zhenfang Zhu & Peiyu Liu & Peipei Wang, 2019. "Influence Maximization in Social Network Considering Memory Effect and Social Reinforcement Effect," Future Internet, MDPI, vol. 11(4), pages 1-16, April.
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    15. 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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