Modeling user interest and community interest in microbloggings: An integrated approach

Abstract

To explain why a user generates some observed content and behaviors, one has to determine the user’s topical interests as well as that of her community. Most existing works on modeling microblogging users and their communities however are based on either user generated content or user behaviors, but not both. In this paper, we propose the Community and Personal Interest (CPI) model, for modeling interest of microblogging users jointly with that of their communities using both the content and behaviors. The CPI model also provides a common framework to accommodate multiple types of user behaviors. Unlike the other models, CPI does not assume a hierarchical relationship between personal interest and community interest, i. e., one is determined purely based on the other. We build the CPI model based on the principle that a user’s personal interest is different from that of her community. We further develop a regularization technique to bias the model to learn more socially meaningful topics for each community. Our experiments on a Twitter dataset show that the CPI model outperforms other stateof-the-art models in topic learning and user classification tasks. We also demonstrate that the CPI model can effectively mine community interest through some representative case examples.