Predicting user participation in social networking sites

Social networking sites provide a convenient way for users to participate in discussion groups and communicate with others. While users situate in and enjoy such a social environment, it is important for various security related applications to understand, model and analyze participating users´ behavior. In this paper, we make an attempt to model and predict user participation behavior in discussion groups of social networking sites. Our work employs a feature-based approach, which considers four types of features: thread features, content similarity, user behavior and social features. We conduct an empirical study on a popular social networking site in China, Douban.com. The experimental results show the effectiveness of our approach.