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Consensus Reaching Based on Social Influence Evolution in Group Decision Making.

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    This study introduces a social influence evolution model for social network group decision making (SNGDM). It proposes a consensus reaching process based on this evolution, demonstrating its effectiveness and advantages.

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    Area of Science:

    • Social Network Analysis
    • Decision Making Science
    • Computational Social Science

    Background:

    • Determining individual weights (social influences) is crucial in social network group decision making (SNGDM).
    • Individual social influences can dynamically change over time in SNGDM.
    • Reaching consensus is a significant challenge in SNGDM.

    Purpose of the Study:

    • To model the natural evolution of social influence in SNGDM.
    • To develop a consensus reaching process that accounts for evolving social influences.
    • To demonstrate the applicability and advantages of the proposed method.

    Main Methods:

    • Established a social influence evolution model combining intrinsic and network influences.
    • Designed a consensus reaching process based on social influence evolution (CRP-SIE).
    • Utilized a hypothetical application and simulation analysis for validation.

    Main Results:

    • The social influence evolution model effectively captures dynamic changes in individual weights.
    • The CRP-SIE method facilitates consensus reaching in evolving social networks.
    • Simulation analysis confirmed the impact of social influence evolution on consensus and showed the proposal's superiority.

    Conclusions:

    • Social influence naturally evolves in SNGDM, impacting group consensus.
    • The proposed CRP-SIE offers an effective approach for consensus reaching in dynamic social networks.
    • The model and process provide valuable insights into SNGDM dynamics.