Research On Situational Awareness Of Rumor Topic Propagation Based On Social Network

With the emergence and rapid development of social networks,online social networks is becoming a more important way of communication than traditional social networks.Although social networks bring great convenience to people in communication,the openness and autonomy of social networks also lead to the rapid spread of rumors and other negative news,which poses a great threat to social harmony and stability.Therefore,it is necessary to make an in-depth study on the propagation law and trend of rumor information in social networks and then formulate corresponding countermeasures.This thesis mainly studies the internal propagation law and the overall propagation trend of rumor topic from the microscopic and macroscopic perspectives.The contribution of this thesis can be summarized as follows:1.In terms of individual user behavior and rumor spreading rules,aiming at the adversarial game relationship of rumor and anti-rumor in the process of spreading,and taking into account the advantages of generative adversarial networks in learning data distribution and enhancing data samples,a rumor propagation prediction model based on anti-rumor and generative adversarial networks was proposed.Firstly,considering the sparse data samples of effective cross-countermeasures in the process of spreading rumor and anti-rumor,a model of unsupervised generative adversarial networks is used to enhance homomorphism data in the sample space.Then,aiming at the symbiotic and antagonistic game relationship between rumor and anti-rumor,evolutionary game theory is introduced.The internal and external factors that affect user behavior within rumor propagation are comprehensively considered,and a quantitative rumor-refutation mutual influence model is proposed.Finally,considering the dynamic time limit of rumor and anti-rumor propagation life cycle,a user behavior prediction method based on rumor topic is proposed.2.In terms of user group behavior and rumor spreading situation,aiming at the timeliness characteristics of rumor topic spreading,as well as the problems such as few samples,short period and uncertainty,and considering the advantages of the gray system model in dealing with fewer data and poor information,a prediction model of rumor popularity based on gray system theory is proposed.Firstly,the rumor topic is sliced in time to get the number of rumor forwarding people.Then,based on the sequence of forwarding people,the accumulation generation and mean generation transformation are carried out,and the expression parameters of the grey Verhulst model are estimated by the least square method.Finally,the number of rumor forwarded in the next period is predicted by the proposed model.If the cycle continues,the trend of rumor evolution will be controlled.Finally,the validity and reliability of the model proposed in thesis are verified by the data set of Sina Weibo.Experiments show that the model can effectively explore the internal law of rumor propagation,and predict the situation of rumor propagation.