Utility of decisions and beliefs based on bounded-confidence opinion dynamics with group conformity

Abstract

Political parties, groups and organizations deliberately manipulate the direction of public opinion on social media, causing the evolution of group opinions to become increasingly complex driven by the information fusion mechanisms and artificial intelligence technologies. In this context, we propose a dynamic, heterogeneous bounded social model that integrates external group conformity and internal individual attributes, which simulates the role of individual decision-making abilities and beliefs in the evolution of opinions under different conformity scenarios. In this model, we introduce a network formation game process to simulate how users make judgments under the influence of external conformity, which arises from the complex mechanisms generated by numerous informational factors acting on the group. We find that improving the decision-making abilities and beliefs can reduce the chaos in opinion evolution. In the scenario of informational conformity, the high degree of individual beliefs can suppress opinion fragmentation. Moreover, when the proportion of normative conformity increases, the enhancement of decision-making can further reduce the chaos in communication. Thus, we reveal the pathways that guide the trends of opinion evolution in social networks.