Research On The Evolution Model Of Public Opinion Reversal Based On The Characteristics Of Social Network

In the fields involving social sensitive points or closely related to the interests of the people,the network public opinion is easy to turn,upgrade or fission.It is not difficult to observe that the social network system in the field of public opinion is changing dynamically:opinion leaders,as hub nodes,can output their opinions and influence to ordinary individual users,and when the consistency of individual users’ opinions is affected by more than half of them,it will become the "mainstream opinion" in the organization.At this point,the organizational climate will in turn affect the emotional outlook of the remaining users.When individual users’ sense of belonging to the organization reaches a corresponding degree,they will obey the mainstream view in the group oppression.Therefore,based on such a logical point of view,this paper considers the influence of opinion leaders and organizational climate on public opinion reversal events,and further explores the evolution mechanism of public opinion reversal events under this background.The related research at home and abroad were reviewed in this paper,using literature analysis,and because public opinion inversion and journalism,the histology theory closely linked,so this article combed the involved in the basic theory and according to the actual amount of public opinion in the social network topology characteristics and transmission mode,for a variety of reversal to make such a mood under the type of public opinion analysis,at the end of the paper is based on the simulation results of the empirical case,corresponding countermeasures and suggestions are provided for different roles such as government departments,opinion leaders and the public.Specific research results are as follows:(1)The basic network model as a viewpoint interaction model is built and its differences with other real networks are analyzed.Combining literature analysis with reality,this paper analyzes the important complementary characteristics and three structural characteristics of social networks: user attention pattern,preference connectivity,and the growth and dynamic propagation of variation.Based on these characteristics,a complex network complementary model with high matching degree(classic BA network)is found and modified.Finally,a directed scale-free social network model is designed to distinguish ordinary user groups and opinion leaders groups according to user characteristics and to simulate the information transmission mode in social networks.(2)The evolution model of public opinion reversal based on the characteristics of social networks is constructed and its influencing factors are systematically analyzed.The comprehensive centrality index in social network analysis is used to find opinion leaders hidden in BA network,and the influence weight and opinion update threshold value of each node are determined according to the centrality,and the influence and interaction of each node in social network are reproduced in the digital world.At the same time,we introduce the organizational climate as an influencing factor,and determine the organizational sense of belonging,which plays an important role in organizational climate.Finally,the "artificial meat" inversion event on Sina Weibo was taken as an empirical case,and the experimental data and actual data were compared and analyzed to verify the validity of the model.At the same time,an adjustment experiment is conducted on the values of three control variables,namely the number of opinion leaders,the opinion value of opinion leaders and the sense of belonging of the organization,to explore the reversal of public opinion caused by their fluctuation.Furthermore,it puts forward countermeasures and suggestions to promote the construction of public rational discussion community,prevent and alleviate the escalation of online conflicts,and makes suggestions for the healthy and orderly development of cyberspace public opinion space governance.This paper provides a short-term prediction model to simulate the reversal of public opinion in social networks by constructing the evaluation system of the centrality index of the public opinion evolution model,obtaining the dynamic weight of important indicators,and using the viewpoint interaction system based on BA scale-free network.