Modeling and Forwarding Prediction of Social Network Information Transmission

Abstract

With the continuous progress of network information, the traditional way of information transmission is replaced by social network, and gradually become an important way for people to obtain various types of information. In social networks, network users can spread and receive information to the maximum extent within a reasonable range and conduct interpersonal communication on this basis. The basic data of social network is generated by the original information published by network users, and the transmission of basic data is realized through the forwarding of other users, that is, the effective transmission of social network information. The purpose of this paper is to predict the trend and law of network information dissemination by means of modeling and forwarding prediction of social network information dissemination, so as to promote the positive role of information dissemination. In this paper, the relevant definitions involved in social network are analyzed. On this basis, PCA algorithm is used to accurately analyze the network information data. Then, specific analysis is made on the establishment of the transmission model. The experiments in this paper show that the establishment of the social network information dissemination model is conducive to promoting the accurate prediction of information dissemination and realizing the positive dissemination of network information.