EURO 2025 Leeds
Abstract Submission

2868. A novel dynamic trust network analysis method for consensus reaching in social network group decision making

Invited abstract in session MA-33: Social Networks and Decisions, stream Decision Analysis.

Monday, 8:30-10:00
Room: Maurice Keyworth 1.31

Authors (first author is the speaker)

1. Yan Xu
School of Management, Northwestern Polytechnical University
2. Xinzhu Wu
School of Management, Northwestern Polytechnical University

Abstract

Trust relationships constitute fundamental concept in social network group decision making (SNGDM). This study proposes a novel trust network analysis method addressing dynamic trust relationships in SNGDM. During consensus reaching processes, DMs adjust their opinions based on those they trust more, which reciprocally influences trust levels. Direct trust relationships between DMs are quantified through trust degrees measuring reliability or credibility within the network structure. Opinion adjustments impact these relationships, resulting in adjusted trust degrees derived from initial trust values and opinion similarity. Indirect trust relationships are determined through direct trust and propagation pathways. Given the multiplicity of overlapping paths with common intermediaries, path interactions must be considered. We employ the Choquet Integral to capture interacting effects between trust paths, calculate path weights and aggregate indirect trust degrees. By integrating both adjusted direct and indirect trust degrees, we develop a trust network-based consensus model that enhances stability in consensus building. The proposed method provides precise representation of indirect trust propagation through path interaction modeling and establishes a comprehensive framework integrating both direct and indirect trust relationships. A comparative analysis is conducted to validate the method, demonstrating its efficacy in managing dynamic trust relationships in GDM scenarios.

Keywords

Status: accepted

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