Research On New Social Network Public Opinion Communication And Intervention Model Based On Coupling Network

With the development of mobile communication and artificial intelligence technology,great changes have taken place in the social environment.Public opinion has rapidly become the amplifier and accelerator of social hot issues.On the one hand,the large-scale spread of negative public opinion leads to people's anomie behavior.On the other hand,the rapid spread of positive energy events can enhance more people's social cognition.Through the research on the law of information dissemination and the structure of social network,we can realize the effective governance of public opinion.Traditional research on public opinion communication is not applicable in quantitative analysis,so further research on public opinion communication in the new social environment is of great significance.This paper focuses on the new features of network cross coupling and information dissemination motivation diversification in the new social environment.Focusing on the two concerns of public opinion governance,communication and control,this paper constructs a public opinion dissemination model based on audience portrait and a coupled network public opinion dissemination model in the aspect of public opinion dissemination.In the aspect of public opinion control,the connection relationship is mapped to a single-layer network by combining with the characteristics of the coupled network,and the results are analyzed A key node recognition algorithm based on local centrality is constructed.In order to give the negative public opinion intervention and public opinion positive feedback,positive public opinion promotion strategy suggestions,for the new social environment of public opinion communication and control to build a theoretical framework.This paper mainly includes the following workFirstly,the public opinion communication model based on audience portrait is established.There are many factors that lead to the spread of public opinion.The current research on the influence of the differences of communication subjects on the spread of public opinion is less,or often only consider a single factor.This paper comprehensively considers the basic characteristics of individual cognition,anonymity,authority,herd effect,memory effect and other psychological characteristics,and expands the communication state space,and combines the previous rumor spread model of the rumor From a probability value to a function based on the audience's multi-dimensional portrait,a rumor propagation model based on the audience's portrait in the network is proposed.With the help of cellular automata,the model is established,and then the propagation law of social network public opinion which is more in line with the real scene is studied.The simulation results show that the basic characteristics such as the audience's cognition and the psychological characteristics such as the herd effect have a great impact on the spread of rumors.Through the empirical verification of "red yellow blue kindergarten child abuse incident",it shows that the model is consistent with the real spread situation and has strong effectiveness.Finally,based on the model,the governance enlightenment of public opinion layer communication is obtained.Secondly,a coupling network model based on the age of the audience is proposed,and the characteristics of its communication dynamics are analyzed.Under the new social environment,coupling interaction between real society and online virtual social network is common,so it is necessary to expand from single analysis of online social network public opinion propagation to coupling network.This paper analyzes the characteristics of normal distribution of age structure in online social networks,constructs a two-layer network of online virtual and offline reality based on the coupling of age characteristics,and further studies the public opinion communication mechanism under the coupling network according to the communication psychology,namely,the communication state updating step by step,the state tightly coupled,and the state transition between layers follow the "offline cause online resonance" and "online resonance" This paper explores the public opinion communication on the two-tier social network,and more accurately describes the public opinion communication behavior in the real social network environment.Finally,through the "public opinion of Yuhang Sino Thai waste incinerator" public opinion to carry out empirical verification,the model proposed in this paper has a good reduction of the scene,proving that this model has a strong effectiveness and advanced nature in the propagation process of public opinion incidents.Finally,the key node identification model is constructed to expand the social network public opinion control method.Coupled social networks share the same node space.By mapping different layer topological relationships to single-layer network,the related research is carried out with the help of single-layer network key node identification model.This paper analyzes the advantages and disadvantages of classical key node recognition algorithms,and proposes a local central key node recognition algorithm for social networks based on the characteristics of information dissemination,especially the influence of "bridge" and "false core" nodes on recognition accuracy.The algorithm improves the calculation method of "structural hole" constraint value through the aggregation and diffusion of nodes and their neighbors,and further evaluates the importance of nodes by combining the location information identified by K-shell decomposition algorithm.Through the verification of five real social networks such as dolphins,the proposed algorithm can effectively eliminate the influence of class core and identify important"bridge nodes" with fine-grained.The algorithm has obvious advantages over traditional algorithms.After removing the identified key nodes,the network clustering coefficient decreases and the average path length increases.The changes of these network characteristics can control the expansion of information propagation range,and the information from the identified key nodes can effectively expand the propagation range.Finally,the microblog data of "Zhai Tianlin academic misconduct" is sampled and the communication network is constructed,which proves that the algorithm can accurately identify the key communication nodes in the real public opinion events.Through this model,the negative public opinion can be effectively intervened,and the positive public opinion can be quickly spread,which provides a theoretical basis for effectively improving the public opinion governance ability.