The research on topic detection of microblog based on TC-LDA

Abstract

With the rapid development of microblog, the research of topic detection has been paid more attention, which has begun to transfer from the traditional news media to microblog. However, compared with the traditional fields where topic detection applied, the microblogging data is written informally and the structure of that is not rigorous, which will bring great difficulties. In the process of topic detection, there will be lots of noise information extracted as the topics if using the traditional methods. Therefore, based on the Latent Dirichlet Allocation (LDA) model, the Topic-Coreterms Latent Dirichlet Allocation (TC-LDA) model for topic detection is proposed. With considering the microblogging features, the model increases a layer of background model to reduce the noise in microblogging data. The experiment shows that through the method of extending, the model can obtain good results and improve the generalization performance in the same environment.