Wang, Philips Fu LeePhilips Fu LeeWangXie, HaoranHaoranXieWu, Z.Rao, Y.Li, X.Li, J.2021-07-072021-07-072015https://repository.sfu.edu.hk/handle/sfu/783As an important medium used to describe events, the short text is effective to convey emotions and communicate affective states. In this paper, we proposed a classification method based on probabilistic topic model, which greatly improve the performance of sentimental categorization methods on short text. To solve the problems of sparsity and context-dependency, we extract hidden topics behind the text and associate different words by the same topic. Evaluation on sentiment detection of short text verified the effectiveness of the proposed method.enconference proceedings10.1007/978-3-319-22324-7_7