’ s repository of research publications and other research outputs Automatically extracting polarity-bearing topics for cross-domain sentiment classification Conference Item

Joint sentiment-topic (JST) model was previously proposed to detect sentiment and topic simultaneously from text. The only supervision required by JST model learning is domain-independent polarity word priors. In this paper, we modify the JST model by incorporating word polarity priors through modifying the topic-word Dirichlet priors. We study the polarity… CONTINUE READING