Research Of The Microbloggers’ Following Recommendation And Ranking Strategy

With the rapid development of the Internet, the recent years have witnessed an explosion of microblog as a new hot killer SNS (Social network service) application. Actually, the microblog is more widely applied, more functional and more influence. It also narrows the gap between users and services and provides convenient information processing for microbloggers. This paper based on the data source from the Weibo.com, after analysing the distinction between microblog and traditional SNSs, summarizes some new features of the microblogging service. In addition, the analysis of the two types of users’ indicators established the foundation for the subsequent research of this paper. The research works of this paper include following recommendation and ranking strategy.Firstly, microblogging users can follow other users at will to receive their status and tweets. For establishing a reliable following relationship between the users and enhancing the users’reliance on the microblogging, it is an effective means to recommend high-quality following objects for user. This paper analyzes the differences between microblogging and other social network services and constructs a following recommendation model which fuses with the new configuration of social networks. Experiment result shows that the model uses thresholds to filter users firstly, and then two sub models provide following objects with different intimacy and raise the number of following effectively.Additionally, because of its locating of targeted users and the need of the website’s developing, monotonous index is widely used as the foundation of microbloggers’ranking. However, this type of ranking is hard to reflect the microbloggers’real activity in the service, since the differences between microblogging and other SNS (Social Networking Services). This paper focuses on two types of users’distributional feature and message propagation in Sina microblogging and Twitter. The model of how to compute the active index of microbloggers is also given. According to the experiments and analyzes, active index is capable of reflecting the characteristics of active microbloggers, which is suitable for the measurement of active microbloggers’ ranking.