Modeling Of Opinion Dynamics On Two-layer Networks Under Multiple Influences

With the rapid development of the Internet,online social media and offline network with interpersonal relationships together constitute the external environment for the evolution of public opinion.However,most of the current research on the evolution of public opinion is carried out in single-layer networks.In addition,the influence between individuals in social networks can be affected by a variety of factors.However,the traditional methods of measuring individuals' influence mainly consider the topological characteristics of nodes,ignoring the effect of the diversity of individuals' social attributes and different characteristics of online and offline networks on individuals' influence to a certain extent.Therefore,it is of great significance to study the evolution principles of public opinion in the coexistence of offline network and online virtual network,and to explore the measuring method and functions of individuals' multiple influences.This paper firstly constructs a two-layer network,consisting of an offline network and an online network.The nodes in the offline network are in correspondence with online network.The offline network is an improved CTAN network,which considers the similarity edge breaking principle based on the small-world network with generic linking and variation linking.The online network is generated by a scale-free network.Based on the two-layer network model,an improved HK model considering multiple influences is constructed in this paper,that is MIHK model.Multiple influences reflect the different influences of individuals in online and online network on other individuals,determined by the social attributes of individuals and social relationships between individuals.Therefore,multiple influences are weighted by individuals' social similarity and public authority in this paper.In addition,based on the classical HK model,the MIHK model considers the combined effects of multiple influences and confidence bound on the evolution of opinion,and improves the neighbor selecting rule and opinion updating rule.In this paper,multiple influence and its composition,confidence bound,the weight of multiple influence and other factors are analyzed.The experimental results show that the multiple influence of individuals in the two-layer network will affect the evolution of public opinion.Under the appropriate influence threshold,MIHK model is more likely to reach consensus,and the weight of social similarity in online network is smaller than that in offline network.Compared with the classic HK model and MHK model,it takes less time for MIHK model to reach stable.In addition,the influence of online network and offline network on opinion is different.Online network has become the main front for the evolution of public opinion to drive the offline network working together on opinion evolution,and offline network plays a supporting role in the evolution of opinion.The above results can provide theoretical reference for the study of public opinion evolution considering individual complex social attributes and interpersonal relationships.