Research On The Spreading Model And Intervention Of Public Opinion In Online Social Network

The rapid spread of mobile intelligent terminals and blowout growth of online social networks have provided people with a convenient platform to share information anywhere and anytime,further urging network public opinion to become the most active form of social public opinion.In particular,when the network public opinion involves hot social issues,it can easily cause the resonance of netizens and the widespread of the network public opinion.Besides,it may even trigger emergencies and chain reactions,which will challenge the government?s ability to govern and control the network public opinion,and pose a serious threat to the security and stability of the country.According to the research idea of “feature extraction-propagation rule revelation-intervention and guidance”,this paper takes network public opinion propagation modeling as the focus,regards network public opinion intervention as the destination.Firstly,we explore the propagation characteristics of online social network public opinion.Then we reveal the online social network public opinion propagation law from the aspects of individual behavior and group social reinforcement respectively.At last,models of intervention guidance are constructed from two aspects of negative public opinion intervention and positive public opinion influence maximization.This paper provides a comprehensive and systematic analysis of online social network public opinion propagation and intervention problems.It provides theoretical guidance for the government to effectively deal with the propagation of online social network public opinion.The major studies concerned in this paper are as follows:Firstly,mining and extracting characteristics of online social network public opinion propagation.According to the research ideas of “information-network-behavior”,the connotation,characteristics,influencing factors,and life cycle of network public opinion are analyzed.Then,three real online social networks including Douban,Gowalla and Twitter are taken as examples to analyze the basic topological properties such as network average degree,average path length,clustering coefficient.Furthermore,Tencent is taken as an example to analyze the characteristics of user communication behaviors.The features of online public network public opinion propagation are fully extracted.Secondly,online social network public opinion propagation model with information-behavior coupling interaction is constructed.Based on the idea of two-layer network model construction,the propagation mechanism of network public opinion under the interaction of virtual online social network information transmission and social behavior diffusion interaction is analyzed.Then the propagation dynamic model of online social network public opinion with information-behavior coupling interaction is constructed.Moreover,the final spreading size is obtained by solving the basic regeneration number.Finally,an empirical analysis is conducted using the “grabbing salt” storm event triggered by the 2011 Japan earthquake to verify the validity and advancement of the model.Thus the law of online public network public opinion propagation with the information-behavior coupling reinforcement is revealed.Thirdly,an online social network public opinion propagation model considering double social reinforcements is proposed.This paper analyses the effect of positive and negative double social reinforcement mechanism on the individual propagation behaviour.According to the difference of network degree distribution,online social network public opinion propagation models on both homogeneous and heterogeneous networks are proposed.Besides,the spreading threshold and the final spreading size are investigated.Finally,the classical WS small world network and the BA scale-free network are taken as an example to verify the results of the theoretical analysis,and to reveal the law of the online public opinion propagation under the double social reinforcements.Fourthly,a negative network public opinion intervention model considering super spreading mechanism is proposed.We derive dynamic model to describe the intervention process of the negative network public opinion with super spreading mechanism.Then the basic reproduction number and the final size of network public opinion are estimated by the means of Jacobian matrix.Simulations results show that the influence of super spreading mechanism and the force of positive network opinion on the intervention of negative network opinion.Moreover,the intervention measures of online social network negative public opinion with the super spreading mechanism are put forwardFinally,a Local Relative Strength(LRS)method identifying multiple influential spreaders to maximum the spreading influence of positive netwotk public opinion is proposed.The positive public opinion propagation model is applied for four empirical online social networks including Facebook,Email,Blogs,and MSN networks to evaluate the performance of the LRS method.The results show that the LRS method could provide an effective way to identify the multiple influential spreaders in online social networks,which is helpful for government to guide the network public opinion propagation.