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A Rumor Spreading Model considering the Cumulative Effects of Memory

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  • Yi Zhang
  • Jiuping Xu

Abstract

This paper proposes a rumor spreading model which examines how the memory effects rate changes over time in artificial network and a real social network. This model emphasizes a special rumor spreading characteristic called “the cumulative effects of memory.” A function reflecting the cumulative memory effects is established, which replaces the constant rate of memory effects in the traditional model. Further, rumor spreading model simulations are conducted with different parameters in three artificial networks. The results show that all the parameters but the initial memory rate of memory effects function have a significant impact on rumor spreading. At the same time, the simulation results show that the final size of the stiflers is sensitive to the average degree when it is small but is not sensitive to when the average degree is greater than a certain degree. Finally, through investigations on the Sina Microblog network, the numerical solutions show that the peak value and final size of the rumor spreading are much larger under a variable memory effects rate than under a constant rate.

Suggested Citation

  • Yi Zhang & Jiuping Xu, 2015. "A Rumor Spreading Model considering the Cumulative Effects of Memory," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-11, January.
    • Handle: RePEc:hin:jnddns:204395
    DOI: 10.1155/2015/204395
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    Cited by:

    1. Yanlan Mei & Yan Tu & Kefan Xie & Yicheng Ye & Wenjing Shen, 2019. "Internet Public Opinion Risk Grading under Emergency Event Based on AHPSort II-DEMATEL," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    2. Shihang Wang & Zongmin Li & Yuhong Wang & Qi Zhang, 2019. "Machine Learning Methods to Predict Social Media Disaster Rumor Refuters," IJERPH, MDPI, vol. 16(8), pages 1-16, April.
    3. Yin, Fulian & Pang, Hongyu & Xia, Xinyu & Shao, Xueying & Wu, Jianhong, 2021. "COVID-19 information contact and participation analysis and dynamic prediction in the Chinese Sina-microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    4. Jain, Lokesh, 2022. "An entropy-based method to control COVID-19 rumors in online social networks using opinion leaders," Technology in Society, Elsevier, vol. 70(C).
    5. Li, Ming & Zhang, Hong & Georgescu, Paul & Li, Tan, 2021. "The stochastic evolution of a rumor spreading model with two distinct spread inhibiting and attitude adjusting mechanisms in a homogeneous social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    6. Nwaibeh, E.A. & Chikwendu, C.R., 2023. "A deterministic model of the spread of scam rumor and its numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 111-129.

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