Towards Topic Trend Prediction on a Topic Evolution Model with Social Connection

Hot topics are usually those breaking news discussed most at online forums, especially microblogging systems, such as twitter, which helps to learn user concentration and public opinion. This paper focuses on the problem of predicting emerging hot topics. Previous prediction models usually focus on building the content profile to discover the hot topics, they may neglect the social network function or overlook the keyword feature of the post. In this paper, we address this problem by introducing a combined model using the content and the connection information. We define the concept of topic hotness, introduce the algorithm calculating the hotness with content based hotness and connection based hotness, and finally we predict those emerging hot topics by the hotness evolution model.