Research On Group Consensus Model In Social Network Based On Opinion Evolution

The purpose of group decision-making is to reach consensus.In the era of information explosion and rapid change,the process of reaching group consensus has become more and more complex,and there are a variety of influencing factors that may play a role.Therefore,the combination of traditional group decision-making methods and social network analysis methods to study group consensus decision-making in the context of the Internet is the enrichment and expansion of the existing research.Considering the evolution of views among decision makers in the process of group consensus,the study of group decision-making behavior in social network not only increases the connection between theoretical research and practical situation,but also improves the practical significance of relevant theoretical research,so as to provide reference for the study of practical decision-making behavior.In contemporary society,due to the rapid development and widespread popularization of information technology,communication across time and regions has become people’s daily life.Microblog,Wechat,Zhihu and other social media can connect network users.They can express their opinions anytime and anywhere on the online platform.And they can communicate and interact with other users in real time.The debate on social hot events,the dissemination of positive energy events,product evaluation and recommendation are staged on major social platforms every day.It is precisely because of such extensive participation and active discussion that social problems and personal choices can be easily solved.With the changes of people’s communication methods,the scenes and characteristics of decision-making problems also need to be constantly adjusted to adapt to the actual situation.In this context of social development,decision makers are no longer a single individual,but they are users in the same social network.And there is a certain connection and relationship between them.Therefore,the structural characteristics of the social network,the social relationship and interactive behavior between people are the key to the study of group decision-making behavior.This thesis aims to explore the problem of group decision-making in the context of social networks: the study of group consensus models based on opinion evolution.The main research contents of this thesis are as follows:(1)In order to solve the subjective problem of measuring the initial trust relationship of decision-makers in the related research of social network group decision-making,this thesis proposes a social network group consensus model under static influence relationship based on improved PageRank algorithm.Firstly,the evaluation ability of decision-makers is measured by adding the "mutual judgment" process.And the PageRank algorithm is improved to calculate the social influence of decision-makers,that is,the weight of decision-makers.By objectively and fairly measuring the evaluation ability of participants in the decision-making process,we can improve the fairness and authenticity of the weight solution of decision-makers in the decision-making process.And this also ensures the reliability of the final group consensus results.Secondly,the Steiner point based simulated plant growth algorithm(PGSA)is introduced to aggregate the preference information of decision makers.The preference information of decision-makers in the social network is expressed by Pythagorean fuzzy preference relationship,which expands the expression range of decision-makers.The consensus model of social network group decision-making(SNGDM),which uses the simulated plant growth algorithm to aggregate preference information,not only minimizes the evaluation difference between groups and individuals,but also ensures the highest possible group satisfaction.At the same time,the accuracy of assembly and the efficiency of consensus reaching are improved.Then,according to the opinion evolution model: the De Groot model adjusts the evaluation value of decision makers who do not meet the consensus threshold requirements to obtain a consensus opinion.The decision-making interaction process is considered.A numerical example of product evaluation is used to prove the feasibility and effectiveness of the proposed model.(2)On the basis of the above model,in order to consider the complexity of reality and more truly study and simulate the process of consensus reaching in real life,this thesis introduces the opinion evolution of decision-makers,and then proposes a social network group consensus model under the dynamic influence relationship based on viewpoint evolution.First,an evolution model of decision makers’ evaluation ability is established.In the constructed model,the evaluation ability score between individuals is determined by two factors: the individual’s historical evaluation ability score and the similarity of opinions between individuals.An individual’s similarities of opinions can change over time,and decision makers are more likely to recognize decision makers whose opinions are similar to their own.Therefore,the measure of evaluative ability among individuals also changes over time.Then,the dynamically changing decision maker weights are calculated using the improved PageRank algorithm.On this basis,aggregate decision-maker preference information.In addition,a new consensus feedback mechanism based on opinion evolution is proposed,which refers to the opinions of other decision makers according to the difference in evaluation ability.This more realistically simulates the process of group consensus in real life.The same numerical example is used to prove the feasibility and effectiveness of the model proposed in this thesis.It provides a new perspective for the problem of group consensus in social network.