Analyzing user influence of microblog

There have been various studies on user influence of Twitter. However, for the popular Chinese micro-blogging social service Sina Weibo, there are still quite a few quantitative studies on user influence. In this paper, we analyzed the network of following and followed relations among users on Sina Weibo, and found that both the out-degree distribution and in-degree distribution of the network follow power-law distribution. It is also found that the PageRank values of Sina Weibo user (User PR) follows power-law distribution, too. In order to identify influential on Sina Weibo, we ranked users by the number of followers and User PR respectively. The result shows that verified users may have a higher ranking. By researching the rankings, we found that User PR ranking outperformed ranking by the number of followers on quantifying user influence. Furthermore, we have observed topics on Weibo shared by the top 20 users in the order of followers´ numbers and User PR values. We found that there are a large number of images, videos and links on Sina Weibo and most of the topics are created by reposting from another user.