A Novel Approach for Microblog Message Ranking Based on Trust Model and Content Similarity

With the development of social network such as microblog, the number of microblog users increases rapidly. The problem of information overload caused by a large amount of data generated by users is becoming more and more serious. In order to mine the messages which specific users are interested in, we measure social relationship and interactive relationship of users respectively in this paper and propose the trust model based on the user’s direct trust and indirect trust. By means of the trust model, we select the specific user’s candidate user set from a large number of users. We measure the content similarity of messages in the candidate user set and propose a message ranking approach based on user trust model and content similarity. We analyze and compare the ranking results with users’ real behavior in microblog platform. The experiment results show that the approach can accurately rank the microblog messages which the specific users are interested in.