A novel negative feedback information dissemination model based on online social network

Due to the existing social network information dissemination model does not consider the influencing factors of node feedback information. The characteristics of social networks and the social attributes of the disseminators are analyzed; we propose a new social network information dissemination with negative feedback NFSIR (negative feedback susceptible infected removed) model combined with traditional epidemiological models The model first introduces attenuation coefficients and noise coefficients to describe the different effects of information transmission among different users. The feedback function is defined in order to describe the information feedback mechanism. Then, according to the mechanism of information interaction evolution, an information dissemination tree is constructed, and a differential equation of propagation dynamics is established. It reveals the complex interactions and interactions between user relationships, social communities, and cyberspace information in social networks. Finally, the model is applied to two typical real social networks to carry out simulation experiments and compared with the traditional model. Experimental results show that, the intensity of information feedback has a significant impact on the process of information dissemination. It can be seen that the Twitter and Sina microblog networks are significantly different through the analysis of the transmission time and propagation life cycle indicators. The comparison of experimental results shows that the proposed NFSIR model can better reflect the characteristics of real social networks. It proves that the proposed mathematical propagation model is objective, reasonable, and effective. The proposed model not only has strong scalability, but also has application value. It also provides theoretical support for research in related fields.