Modeling And Control Of Network Public Opinion Propagation Based On Edge Deletion And Clustering

The development of online social networks has provided many conveniences for people to obtain and disseminate information.However,the spread of rumors and harmful public opinion information on the Internet will have a huge impact on people's social life.The process of removing rumors and controlling public opinion transmission often requires a lot of manpower and material resources.Therefore,research the network public opinion information transmission mechanism and establish a more suitable model of public opinion communication and adopting effective public opinion communication control methods have important practical significance and social value.The research of complex network theory finds that the dynamic evolution of network structure has an important influence on the spread of network information.This paper analyzes the network structure and finds that the high-density cluster structure in the network can effectively block the cascade of information.Taking into account the behavioral characteristics of individual nodes,such as the social phenomenon that birds of a feather flock together,it shows that we often have the same interests as friends,which makes us tend to keep the same behavior with most friends.Considering that the behavior of nodes will be affected by the behavior of direct neighbors and the propagation characteristics of cascade behavior in the network,a Susceptible-Infected-Susceptible based on Cellular Automata(CA_SIS)model based on cellular automata is proposed.Based on the analysis of the propagation characteristics of the network and the cluster structure in the network,a method for controlling the spread of public opinion on the network with Clusters with link-removed(CLR)is proposed,and simulation experiments are deployed to verify and analyze the effectiveness.The main research work of this thesis is:1.Propose a CA_SIS model of public opinion communication based on cellular automata.Existing information propagation models based on the average field method are difficult to reflect the state of nodes in the network and the evolution of the network topology at each moment,however cellular automata could effectively overcome this deficiency.So this thesis uses the cellular automaton to establish public opinion information propagation model.Considering the characteristics of the information cascade and the influence of surrounding friends on our own behavior,this paper sets dynamic propagation rules to reflect the state transition between nodes,and establishes a CA_SIS propagation model based on public opinion information cascade.2.This paper proposes a CLR method for public opinion propagation control of edge-cutting clustering.Considering the influence of network structure optimization on the control of information dissemination,the characteristics of the network structure that affect the information cascade behavior are analyzed.It is found that the high-density cluster structure in the network can effectively hinder and delay the information cascade behavior.The CLR method achieves the blocking and control of public opinion transmission by deleting or controlling a limited number of edges while ensuring network connectivity.3.Simulation results show that the CA_SIS public opinion cascade model proposed in this paper is more in line with the law of public opinion information spread in real life.In small and medium-sized networks with obvious community structures,the CLR method proposed in this paper can effectively delay the speed of public opinion transmission and control the scope of public opinion transmission.With the same number of deleted edges,the control effect of public opinion communication is significantly better than other edge deletion methods.In short,this thesis focuses on the control of Internet public opinion communication.Considering the cascading characteristics of Internet public opinion communication,a CA_SIS propagation model based on public opinion cascade is established,and a CLR method of edge deletion clustering is proposed based on the characteristics of public opinion transmission in the network.Experimental results show that the method can effectively delay the speed of public opinion transmission and control the scope of public opinion transmission.The method is easy to deploy and can be widely applied to all aspects of network information transmission control.