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Information Spreading Considering Repeated Judgment with Non-Recursion

Author

Listed:
  • Yufang Fu

    (School of Economics & Management, Zhejiang Ocean University, Zhoushan 316022, China
    These authors contributed equally to this work and should be regarded as co-first authors.)

  • Bin Cao

    (School of Management, Xi’an University of Architecture & Technology, Xi’an 710055, China
    These authors contributed equally to this work and should be regarded as co-first authors.)

  • Wei Zhang

    (School of Management, Xi’an University of Architecture & Technology, Xi’an 710055, China)

  • Zongwei Luo

    (BNU-UIC Institute of AI and Future Networks, Beijing Normal University, Zhuhai 519000, China
    Faculty of Science and Technology, Hong Kong Baptist University-Beijing Normal University United International College, Zhuhai 519000, China)

Abstract

This paper investigates an information spreading mechanism under repeated judgment. In a generalized model, we prove that given a necessary condition, information under repeated judgment can sustain continuous spreading. Furthermore, we generalize the aforementioned spreading model on heterogeneous networks and calculate the analytic solution of the final state, in which spreaders finally have a stable scale to ensure that information can continuously spread when repeated judgment of information takes place. Moreover, the simulation results show that the more neighbors the spreaders have, the quicker the information vanishes. This finding suggests that in terms of information spreading under repeated judgement, it is not better to have more neighbors, quite contrary to common opinion.

Suggested Citation

  • Yufang Fu & Bin Cao & Wei Zhang & Zongwei Luo, 2022. "Information Spreading Considering Repeated Judgment with Non-Recursion," Mathematics, MDPI, vol. 10(24), pages 1-16, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4688-:d:999630
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    References listed on IDEAS

    as
    1. Cao, Bin & Han, Shui-hua & Jin, Zhen, 2016. "Modeling of knowledge transmission by considering the level of forgetfulness in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 277-287.
    2. Yang, Dingda & Liao, Xiangwen & Shen, Huawei & Cheng, Xueqi & Chen, Guolong, 2018. "Modeling the reemergence of information diffusion in social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1493-1500.
    3. Bin Cao & Qingyu Zhang & Mei Cao, 2022. "Optimizing Hybrid-Channel Supply Chains with Promotional Effort and Differential Product Quality: A Game-Theoretic Analysis," Mathematics, MDPI, vol. 10(11), pages 1-21, May.
    4. Kawamoto, Tatsuro & Hatano, Naomichi, 2014. "Viral spreading of daily information in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 34-41.
    Full references (including those not matched with items on IDEAS)

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