On the rise and fall of Sina Weibo: Analysis based on a fixed user group

Micro-blogging service Sina Weibo in China has become the country´s most free-flowing and important source of news and opinions just a few years ago. Following its launch in the summer of 2009, Sina Weibo grew quickly, attracting hundreds of millions of users and saw its biggest boom around 2011. However, several reports indicate a decrease in activity on Sina Weibo. In our study, we reveal the prosperity and decline of Sina Weibo by analyzing how a fixed user group´s collective behaviors change throughout the whole development process. A huge dataset based on Sina Weibo along with search engine data is used in this study. In this paper we model the popularity of single tweet and multiple tweets. Then we define the statistic representing the capability of information propagation of Sina Weibo. The well-known time series prediction model, ARMA, is used to model and predict its trend. In addition, we extract both internal features, i.e. features of Sina Weibo, and external features, i.e. public´s attention. Their trends are presented and analyzed. Then detailed experiments are conducted to measure the correlation and causality between them and our proposed statistic. The approaches we present in this paper clearly show the prosperity and decline of this microblogging community.