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ISRT rumor spreading model with different influence mechanisms in social networks

Author

Listed:
  • Hongmei Wang

    (Shandong Province Key Laboratory of Wisdom Mine Indormation Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China)

  • Liqing Qiu

    (Shandong Province Key Laboratory of Wisdom Mine Indormation Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China)

  • Chengai Sun

    (Shandong Province Key Laboratory of Wisdom Mine Indormation Technology, College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China)

Abstract

Rumor, as an important form of information dissemination, has always been a research hotspot in the field of complex networks. How to better understand the rules of rumor propagation and establish a practical dissemination model is a significant challenge. To further study the state transfer in information transmission, this paper established the Ignorant-Spreader-Stifler-Transition (ISRT) model, introduced different influence mechanisms and calculate the influence rate accurately by function. Specifically, (1) Based on SIR model, this paper introduces the transition state, considering that transition may awaken spontaneously to spread rumors due to individual cognition. In this paper, the ratio of the current communicator and the degree of doubt of the transition are introduced into the spontaneous arousal function. (2) This paper redefines the propagation probability function and the forgetting probability function, and introduces the time function to describe the rate from the propagator to the restorer. (3) Due to the presence of highly emotional leader propagators in the network who would awaken the immune to spread rumors again, the model added a link from the recovering person to the infected person. Finally, the nonpropagation equilibrium point E0 and propagation equilibrium point E1 are obtained by establishing the mean field equation. The experimental results show that different influencing mechanisms can more accurately locate the stage change of rumor transmission, which provides theoretical support for more effective control of information transmission.

Suggested Citation

  • Hongmei Wang & Liqing Qiu & Chengai Sun, 2023. "ISRT rumor spreading model with different influence mechanisms in social networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-18, January.
    • Handle: RePEc:wsi:ijmpcx:v:34:y:2023:i:01:n:s0129183123500031
    DOI: 10.1142/S0129183123500031
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    Cited by:

    1. Tan, Jipeng & Zhang, Man & Liu, Fengming, 2024. "Online-Offline Higher-Order Rumor Propagation Model Based on Quantum Cellular Automata Considering Social Adaptation," Applied Mathematics and Computation, Elsevier, vol. 461(C).
    2. Shan Yang & Shihan Liu & Kaijun Su & Jianhong Chen, 2024. "A Rumor Propagation Model Considering Media Effect and Suspicion Mechanism under Public Emergencies," Mathematics, MDPI, vol. 12(12), pages 1-23, June.

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