Research On Mechanism Of Information Dissemination Based On Social Network

Social media is a platform for sharing ideas, experience and opinions. Socialmedia has a critical mass of users. Users communicate, release, share, collaborateand disseminate information each other, generate an enormous amount of usergenerated content named UGC. In recent years, social media is growing rapidly.Facebook, Twitter, Sina Weibo, Tencent Weibo’s users reach one billion,five-hundred million, four-hundred million and five-hundred million respectively.UGC information presents network cross diffusion on social network. As thenumber of forward increases, propagation speed presents exponential growth.Social media’s internal structure is social network. Social network isbringing a profound impact and change on the mode of information dissemination,people’s new way of socializing and popular lifestyle. Social network has been ahot area of research for academic and industry. Although the social network hasbeen very popular, it is not spread for a long time and there are a lot of problemsneeded to be solved urgently. For example, the models of information disseminateon social network, the mechanism of information dissemination and so on. Thispaper focuses on the problems of information dissemination on social network.These research results can be widely used in the prediction of informationdissemination, the perception of dissemination situation, the personalizedinformation recommendation, precision advertising and so on. It also can be usedto find out the illegal users and information to ensure the security of network andinformation.The main important work of this paper includes:(1)In the aspect ofdissemination mechanism analysis, comparing the differences of social networkand other network structures deeply, analyzing the particular mechanism ofinformation dissemination on social network. Based on the above analysis results,this paper proposes the algorithm of information dissemination tree generating. (2)In the aspect of building dissemination model, introducing network dynamicsmodel and epidemic model of epidemiology, and applying them on the large-scaledata of the famous Chinese social network websites (Sina Weibo), meanwhileproposing seven kinds of dissemination model.(3)This paper proposes theinformation topology analysis method. The method of information disseminationanalysis based on information breadth threshold can focus on the informationdissemination. Simultaneously user node analysis based on disseminationtopology can analyze users’ connections, behaviors and concern.(4)By mergingabove improved methods in three aspects together, social network informationdissemination system named SNIDAS is designed and implemented. SNIDASincludes multi-source data acquiring module, information dissemination treegenerating module, dissemination model on social network analyzing module andinformation topology analyzing module. Through experimental evaluation,SNIDAS can insight and analyze the mechanism of information dissemination onsocial network effectively.