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A Multi-Step Interaction Opinion Dynamics Group Decision-Making Method and Its Application in Art Evaluation

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  • Yingtian Li

    (Taiyuan Normal University, China)

Abstract

Due to the development of intelligent decision-making, social network group decision making (SNGDM) has become increasingly valued. Self-persistence is a significant topic in SNGDM problems, while it is ignored in most existing research. Besides, existing opinion evolution models often ignore high-order interactions because they assume individuals only communicate with their friends or neighbors. With these issues in mind, the authors propose a multi-step interaction opinion dynamics model to manage the consensus in SNGDM problem with self-persistence evolution. Given the decision makers' social network information, the centrality degree, interaction strength, and high-order interactions are combined to construct a social influence network. Inspired by the social influence model, the authors develop an opinion dynamic consensus model which also describes the evolution of self-persistence in a group of decision makers. Finally, an example and detailed simulation experiment are presented to demonstrate the efficiency of the proposed consensus model.

Suggested Citation

  • Yingtian Li, 2023. "A Multi-Step Interaction Opinion Dynamics Group Decision-Making Method and Its Application in Art Evaluation," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 12(1), pages 1-14, January.
    • Handle: RePEc:igg:jfsa00:v:12:y:2023:i:1:p:1-14
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    References listed on IDEAS

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    1. 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.
    2. Deng-Feng Li & Peide Liu & Kevin W. Li, 2021. "Big Data and Intelligent Decisions: Introduction to the Special Issue," Group Decision and Negotiation, Springer, vol. 30(6), pages 1195-1200, December.
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