Machine Users Detection on Sina Weibo Platform

In recent years, the rapid development of Sina Weibo has made it the representative of many Weibo platforms in China. Sina Weibo has attracted large numbers of users in China because of its fast speed of information dissemination, simple use and many star users. More and more Chinese people get news and share information through Sina Weibo. In addition to the normal users, Sina Weibo also appeared on some machine users, these users are generated in order to create false sentiment, which seriously affected the good order of the Sina Weibo platform. By studying normal users and machine users, this paper extracts eight features, they are the number of followings, the number of followers, the number of Weibos, the number of years using Sina Weibo, Sunshine credit, the number of Weibos you like, the proportion of following others by recommending and the ratio of followings and followers. Naive Bayes classification approach, KNN classification approach and SVC classification approach are used for experiment. The experimental results show that the recall rate of the machine users detection is above 96% and the accuracy rate is above 98%, which validates the validity of the features extracted in this paper.