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Feedback driven message spreading on network

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  • Nian, Fuzhong
  • Liu, Jinshuo

Abstract

This paper focuses on the role of feedback mechanism on message propagation. In this paper, we study the effect of feedback on message propagation in terms of both the motivation of the communicator to propagate the message and the trust of the message recipient in the communicator, and we design a decay mechanism of motivation based on Newton's cooling law. Based on these considerations, we propose a model of message propagation based on the feedback mechanism. We verify the effect of feedback on message propagation by performing numerical simulations in the Watts-Strogatz (WS) and Barabasi-Albert (BA) networks. The simulation results show that the feedback mechanism leads to faster and more persistent message propagation and that the degree of influence on message propagation varies across different network structures. The simulation also results show that the feedback mechanism changes the structure of the social network and makes the nodes between the networks more closely connected.

Suggested Citation

  • Nian, Fuzhong & Liu, Jinshuo, 2021. "Feedback driven message spreading on network," Chaos, Solitons & Fractals, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:chsofr:v:149:y:2021:i:c:s0960077921004197
    DOI: 10.1016/j.chaos.2021.111065
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    References listed on IDEAS

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    1. Zhang, Jiancheng & Sun, Jitao, 2014. "Stability analysis of an SIS epidemic model with feedback mechanism on networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 24-32.
    2. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
    3. Satsuma, J & Willox, R & Ramani, A & Grammaticos, B & Carstea, A.S, 2004. "Extending the SIR epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 369-375.
    4. Gao, Lei & Li, Ruiqi & Shu, Panpan & Wang, Wei & Gao, Hui & Cai, Shimin, 2018. "Effects of individual popularity on information spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 32-39.
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    Cited by:

    1. Liu, Guocui & Nian, Fuzhong, 2025. "Impact of peer pressure on higher-order network dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 200(P1).

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