Modeling And Analysis Of Fuzzy Opinion Dynamics With Opinion Leaders

In social phenomena,opinion is a crucial factor that affects human decision-making behavior,so it is of great theoretical significance to study the evolution dynamics of opinion.Opinion dynamics based on the multi-agent modeling method to study the evolution process of individuals' opinions in social group based on certain interaction rules.In order to analyze and explain the evolution of opinions,this paper based on the Heglsemann-Krause(HK)model of the bounded confidence rules,comprehensively using fuzzy inference,complex networks,opinion dynamics and other theories,to study the physical laws of group opinions' evolution in the context of uncertain opinions and interaction rules,committed to providing a theoretical basis for the effective guidance and control of public opinion communication.The research content of this article mainly includes the following three aspects:1.Based on the classic HK model,one opinion dynamic model with heterogeneous confidence levels is built,and study the evolution of opinions when there are individual differences among social group.First,considering the complex physiological and psychological characteristics of individuals,which may lead to individuals having different levels of trust and the existence of asymmetric influence relationships between individuals,a dynamic model of non-uniform bounded trust perspective is established.Second,considering the degree of influence of individuals on their neighbors,the entire group is divided into two categories of dominant layer individuals(public opinion leaders)and subordinate layer individuals(ordinary individuals),and a non-uniform bounded trust perspective based on dominant-subordinate model.2.A HK model with fuzzy rules is built and we analyze its dynamic evolution rules.The individuals in the group are divided into two categories: dominant-level individuals and subordinate-level individuals,and considering the fuzzy inference relationship between individuals' opinion gaps and individuals coupling weights,the coupling weights between individuals are determined according to the intimacy between individuals.Compared with the model in the previous chapter,the model in this chapter takes into account the actual situation of different intimacy between individuals,which makes the model in this chapter closer to real life.3.A fuzzy HK model based on social network and opinions interaction network is established,and we analyze the evolution of group opinions on a complex network.First,based on a complex network,a social relationship network between social individuals is established,and the social relationship between individuals(such as friendship,classmate relationship,etc.)is characterized by a scale-free network,and individuals with large moderate nodes in the network are called opinion leader.Secondly,an opinion interaction network for presenting individual opinion communication rules is established,and fuzzy inference is used to establish individual opinion update rules.This model not only considers the degree of intimacy between individuals,but also uses the special network characteristics of complex networks,which can effectively describe the complex connections and relationships between individuals in real life.