Social network utility consensus model with empathic and fuzzy interactions

In social network group decision-making, interactions between decision makers are the basis for the formation of a sufficient consensus. Based on the traditional minimum cost consensus models, this study adopts Choquet integral and empathy theory to consider interaction constraints that exist in the integration of a consensus opinion and the evolution of opinion adjustments. We employ social network structures, interaction characteristics, and influence indices as weight constraints to study the convergence law of social network cost consensus, and apply piecewise-linear utility functions to fit the heterogeneity and stage characteristics of decision makers' attitudes. Three cost consensus models of social utility maximization are constructed with consideration of fuzzy interaction, empathic interaction, and a mixture of fuzzy and empathic interactions, respectively. And this paper extracts the correlation between traditional cost consensus models and cost consensus models with interaction. A case analysis of emergency material reserve decision-making explains the good applicabilities the constructed models in this paper.

Automated summary

In social network group decision-making, interactions between decision makers play a crucial role in achieving sufficient consensus. This study combines traditional cost consensus models with Choquet integral and empathy theory to consider interaction constraints in opinion integration and adjustment evolution. By incorporating social network structures, interaction characteristics, and influence indices, the convergence law of social network cost consensus is investigated. Different cost consensus models, including fuzzy interaction, empathic interaction, and a combination of both, are constructed using piecewise-linear utility functions to capture the heterogeneity and stage characteristics of decision makers' attitudes. A case analysis of emergency material reserve decision-making demonstrates the applicability of the proposed models.