A tweets recommendation algorithm based on user relationship and text emotional tendentiousness

Micro-blog, also known as twitter, is a platform which is based on user relationships for information sharing, spreading and obtaining. So how to share the messages in micro-blog efficiently based on the users´ interest with analyzing the user information has become a key research topic. According to the analysis of the micro-blog user relationship and the theory of Analytic Hierarchy Process in the management science, this paper establishes a user influence model, to help explain how the target users affect the core user. With the combination of Word Activation Forces Theory, we put forward an algorithm to express the emotional tendentious of each noun-word in all the tweets. In addition, we calculate and find the corresponding tweets to recommend to the core user and the experiment in this paper proves the effectiveness of the algorithm.