Fuzzy Opinion Dynamics-Driven Consensus Model within Hybrid Meso–Scale Structure in Social Trust Network

Large-scale group decision making (LSGDM) provides an effective way to obtain desirable group decision outcomes. Many studies have neglected the effect of opinion dynamics on the consensus reaching process (CRP) in social trust network (STN) with hybrid meso-scale structure. Additionally, the application of communication theory to CRP has rarely been considered. This paper is devoted to building a fuzzy opinion dynamics-driven consensus model through the detection of hybrid meso-scale structures. First, this paper proposes a novel meso-scale structure detection method that can detect both overlapping community structures and core-periphery structures in STN. Then, to capture the opinion dynamics process under hybrid meso-scale structures, this paper improves the opinion dynamics model by delineating five categories of nodes. Considering the dynamic changes of CRP, a consensus feedback mechanism driven by opinion dynamics is proposed. In addition, the opinion adjustment is based on the ‘Spiral of Silence Theory’. Finally, the practicality of the proposed model is illustrated through an example. And the superiority of the new detection algorithm and the efficiency of the novel consensus model are demonstrated through comparative analysis.