Modeling Opinion Evolution and Conformity Behavior in Large-Scale Social Network Group Decision-Making
本文提出一个观点演化模型，模拟从众行为对群体观点形成的影响，通过权重分配、关系传播和演化分析，在公共卫生政策实验中验证了模型的有效性和稳定性。
Individual interactions and conformity play a crucial role in shaping group opinions and influencing the decision-making process. This article introduces a novel opinion evolution model to simulate the impact of conformity on group opinion formation, focusing on weight allocation, relationship propagation, and evolution analysis. In the weight allocation phase, individual weights are evaluated using network structure and the PageRank algorithm. For relationship propagation, indirect trust relationships are computed via a weighted average method, leading to a more precise social network model. In the evolution analysis, an improved Hegselmann–Krause (HK) model demonstrates evolutionary stability. Two types of conformity behavior are simulated: active conformity behavior within clusters and passive conformity behavior via opinion leaders across clusters. Experimental studies on public health policy validate the effectiveness of the proposed model. The results show that this model more accurately captures the complex behavioral patterns of individuals in large-scale social networks and exhibits strong evolutionary stability.