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The effect of social tie on information diffusion in complex networks

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  • Yi, Yinxue
  • Zhang, Zufan
  • Gan, Chenquan

Abstract

Social network is an important carrier of information diffusion, and social tie is one of most significant factors between them. To understand the impact of social tie on information dissemination, a dynamical model with social tie strength and self-confirming mechanism is proposed and analyzed in this paper. Theoretical analysis indicates that the equilibrium of the proposed model is globally asymptotically stable, and social tie plays a key role in information propagation. Finally, some numerical simulations under synthetic networks and a partial Facebook network are given to illustrate the main results.

Suggested Citation

  • Yi, Yinxue & Zhang, Zufan & Gan, Chenquan, 2018. "The effect of social tie on information diffusion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 783-794.
    • Handle: RePEc:eee:phsmap:v:509:y:2018:i:c:p:783-794
    DOI: 10.1016/j.physa.2018.06.063
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    References listed on IDEAS

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    1. Chenquan Gan & Maobin Yang & Zufan Zhang & Wanping Liu, 2017. "Global Dynamics and Optimal Control of a Viral Infection Model with Generic Nonlinear Infection Rate," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-9, February.
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    5. Zhang, Chunming & Huang, Haitao, 2016. "Optimal control strategy for a novel computer virus propagation model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 251-265.
    6. Zhang, Ruixia & Li, Deyu, 2017. "Rumor propagation on networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 375-385.
    7. Wang, Haiying & Wang, Jun & Ding, Liting & Wei, Wei, 2017. "Knowledge transmission model with consideration of self-learning mechanism in complex networks," Applied Mathematics and Computation, Elsevier, vol. 304(C), pages 83-92.
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    Cited by:

    1. Gong, Hao & Guo, Chunxiang & Liu, Yu, 2021. "Measuring network rationality and simulating information diffusion based on network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).

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