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A visual interaction consensus approach for fuzzy social network with trust propagation

Author

Listed:
  • Wei-xue Diao

    (Jiangnan University
    Southeast University)

  • Yong Liu

    (Jiangnan University)

  • Jin-hong Yi

    (Jiangnan University)

  • Xue-ge Guo

    (Jiangnan University)

  • Jun Yang

    (Jiangnan University)

Abstract

With the rapid development of the Internet and the increase in online communication, complex social relationship produces new challenges to group decision making. To deal with the group consensus problems consisting of fuzzy preference information and incomplete trust relationship, considering trust propagation, we exploit the theory and methods of network analysis, clustering, Pythagorean fuzzy set, and group decision making to construct a fuzzy information social network group consensus approach, and discuss four different scenarios of consensus (high–high, high–low, low–high and low–low) between the interest subgroups and whole social network by setting different compromise parameter values for different situations to reduce the supervision cost and keep initial opinions as much as possible. Finally, we use a vaccine selection case to verify the rationality and applicability of the proposed model.

Suggested Citation

  • Wei-xue Diao & Yong Liu & Jin-hong Yi & Xue-ge Guo & Jun Yang, 2025. "A visual interaction consensus approach for fuzzy social network with trust propagation," Fuzzy Optimization and Decision Making, Springer, vol. 24(3), pages 367-396, September.
    • Handle: RePEc:spr:fuzodm:v:24:y:2025:i:3:d:10.1007_s10700-025-09450-4
    DOI: 10.1007/s10700-025-09450-4
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    References listed on IDEAS

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    1. Gong, Zaiwu & Guo, Weiwei & Herrera-Viedma, Enrique & Gong, Zejun & Wei, Guo, 2020. "Consistency and consensus modeling of linear uncertain preference relations," European Journal of Operational Research, Elsevier, vol. 283(1), pages 290-307.
    2. Harish Garg, 2017. "Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 546-571, December.
    3. Zhibin Wu & Xieyu Yang & Jiancheng Tu & Xue Chen, 2020. "Optimal consistency and consensus models for interval additive preference relations: A discrete distribution perspective," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(9), pages 1479-1497, September.
    4. Tang, Ming & Liao, Huchang & Xu, Jiuping & Streimikiene, Dalia & Zheng, Xiaosong, 2020. "Adaptive consensus reaching process with hybrid strategies for large-scale group decision making," European Journal of Operational Research, Elsevier, vol. 282(3), pages 957-971.
    5. Liu, Bingsheng & Zhou, Qi & Ding, Ru-Xi & Palomares, Iván & Herrera, Francisco, 2019. "Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination," European Journal of Operational Research, Elsevier, vol. 275(2), pages 737-754.
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