A Coevolutionary Opinion Model Based on Bounded Confidence, Reference Range, and Interactive Influence in Social Network
The rapid development of Web 2.0 technology has made social network platform become an important place for opinion generation, exchange, and dissemination. Thus, the study of opinion evolution via social network has important theoretical and practical significance. In this paper, we propose an coevolutionary opinion model of social network based on bounded confidence, reference range, and interactive influence. First, a dual opinion structure is defined, which considers both inward attitude and outward appearance to reflect the constitution and expression of individual opinion. Second, the interactive mechanisms between individuals are captured through two types of social relationships as authority and familiarity. Then, each individual is assigned a reference set and a trust set based on the individual influence model and bounded confidence model. In order to connect the micro-opinion update behavior and macro-network evolution phenomenon in such situation, an agent-based coevolutionary opinion model is proposed based on multidimensional time-varying interactive influence of users. Three groups of simulation experiments have been conducted to compare the system dynamics under different values of confidence threshold, reference set size, and social relationship influence. The obtained results are found in good agreement with what has happened in the bounded confidence model, but more accord with the people behavior characteristics of opinion interaction under the network environment, which would help us to better understand the internal mechanism of opinion dynamics and social network evolutions.
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