Topic model-based micro-blog user interest analysis

As a popular Internet information exchange platform, Micro-Blog like Twitter attracts a large amount of users to share information through short and noisy messages. In this paper, we aim to discover Micro-Blog users´ interest using topic model. In the topic model, users´ metadata such as labels are taken as new features and been put into user document which will be used to infer user´s interest. Experimental results indicate that this method gives satisfying user interest and is capable for reality project. This paper also introduce two applications based on user interest detected before: 1) Keywords extraction based on interest (We calculate word entropy using word topic distribution as new feature). 2) User clustering based on user interest.