The Design And Demonstration Of Evolution Model On Micro-blogging Users’ Fans

In2009, the emergence of Sina Micro-blogging opened the development prelude of themicroblogging in China. As a convenient communication tool, the microblogging getsInternet users’ attention and affection more and more with the time shift gradually. Thebooming microblogging also activizes the interest of many scholars,then they studymicroblogging deeply from all aspects, so the fruits of their research have provided theoreticalbasis for people to understand the microblogging thoroughly. However, very few scholarsexplores the variation of the microblogging users’ fans. The number of fans is the majorfactors for corporations to launch marketing in the microblogging, therefore, in order toprovide the reference for corporations to launch marketing in the microblogging, the authorexplores the variation of the users’ fans in Sina Micro-blogging.This thesis used network Modeling and network evolution Methods to study the changeof the users’ fans. First, we mostly summarized the extended research of Scholars at home andabroad for the scale-free network model (BA model)，and reviewed the related theories of thecomplex network. Then, we used the tree diagram to show the types of users,which was thebasis for determining the degree distribution. Afterwards we input the number of fans inExcel, drew a scatter plot, and obtained the degree distribution--a truncated power-lawdegree distribution.Based on the type of degree distribution,we chose the BA model as the basic model.Then,considering the interfering factors of fans, we improved the basic model with AttractivenessMechanisms, then built up a complete users’ fan evolution model. After that, we designed thesimulation processes according as model arithmetic and developed a simulation function byMatlab to check up the validity of the new model. Finally, through comparison of simulateresults with empirical data, we confirmed the validity of the new model.The different microblogging groups are impacted by different factors in of changes indifferent stages. The number of fans depends on their own attractiveness when they enter themicroblogging early; when the new users become the old user as time goes on, their origianlfans and the rate of change of fans in microblogging will influence the increase of fans, thuswe further analyse the correlation of user’s property and the rate of change of property, thenwe expanded the users’ fan evolution model with the conclusion. The most innovation of this thesis is that we use the network modeling approach toanalyze the change of microblogging users’ fans, and build up evolution model,whichprovides a new perspective for future research in this field.