Research Of Public Opinion Formation Model On Social Network

With the rapid development of information technology,Micro-blog,WeChat,Facebook,Twitter and other online social network have become the important way for people to obtain informations,publish opinions and express emotions,which bring great convenience for the spread and evolution of public opinion.The study of the spread and evolution mechanism of public opinion in the social network is of great significance for the supervision and guidance of public opinion.The research of opinion has gradually extended from social communication and psychology field to interdisciplinary fields including information science,complexity science,theoretical physics and so on.From the perspective of complex networks and synergy theory,the internal and external factors in opinion evolution and formation were analyzed in this thesis;then the dynamic model of public opinion is deeply studied.The main works are organized as follows:Firstly,the regular network,random network and small world network can't fully reflect the real social network topology.For this problem,the scale-free network with tunable clustering coefficient was established,which was used as the network carrier of opinion evolution model.Secondly,considering the complexity of interpersonal relationships network and the heterogeneity of individual neighborhood in opinion spreading,a synergistic opinion evolution model was proposed.Through simulation experiments under different parameters,discussed the effects of order parameter and network structure on magnetisability.Experimental results show that order parameter can not only embody the synergy of system powerfully but accord with the real situation fairly.Thirdly,aiming at the universality of individual interaction and the heterogeneity of individual social influence in opinion spreading,an opinion formation model of social network was proposed on the basis of Hegselmann-Krause model.By introducing the concepts of intimacy between individuals,interpersonal similarity and interaction strength,the individual interactive set was extended,the influence weight was reasonably quantified,and then more realistic view of interaction rule was built.Through a series of simulation experiments,the model was discussed and analyzed deeply.The simulation results indicate that group views can converge to the same and form consensus under different confidence thresholds.And the larger the confidence threshold is,the shorter the convergence time is.Meanwhile,extending the interactive set and increasing the strength of interpersonal similarity will promote consensus formation.Besides,when the clustering coefficient and the average degree of scale free network are higher,the group views are more likely to produce convergence effect.