The Research On The Opinion Dynamics Under Mixed Interaction

In recent years,opinion dynamics has aroused extensive interest of scholars in various fields.In theoretical research,it tries to explain the complex social phenomena in real life by defining the opinions of individuals in groups and observing the changes of group opinions.In complex systems,agents often interact with others in two distinct types of interactions,namely,pairwise interaction and group interaction.There are many classical models in the field of opinion dynamics,among which the Deffuant-Weisbuch model(DW model)adopting pairwise interaction and the Hegselmann-Krause model(HK model),which uses group interactions,are two of the most widely studied opinion dynamics.In this paper,we first studied the DW model and the HK model in detail.We found that the two models have different characteristics,therefore we hope to combine these two models in a way to get better results than using only one model.Then we proposed a novel opinion dynamics model and studied the effects of the combination on consensus in the population.In the model,we introduced a parameter ? to control the weights of the two interactions in the system.In this paper,the numerical simulation method was used to study the model.We found that there exists an optimal ?,which can lead to a highest probability of complete consensus and minimum critical bounded confidence for the formation of consensus.In order to further explore the influence of a on opinion formation,we also observed some statistical characteristics of clusters in the system.Moreover,we checked the robustness of the results on different network structures,and found that the promotion of opinion consensus by a is not limited to complete graph,but also ER random networks.