Open AccessModeling and Forwarding Prediction of Social Network Information Transmission
Author(s) -
Yanfei Zou,
Shuying Liu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/750/1/012147
Subject(s) - computer science , information dissemination , dissemination , social network (sociolinguistics) , transmission (telecommunications) , information transmission , computer network , data transmission , data science , data mining , world wide web , telecommunications , social media
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.