Joint sentiment/topic model for sentiment analysis

  title={Joint sentiment/topic model for sentiment analysis},
  author={Chenghua Lin and Yulan He},
Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the… CONTINUE READING
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