A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
ArXiv.orgPublished 29 September 2004Open access
Bo Pang, Lillian Lee
Citations660
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Abstract
Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as "thumbs up" or "thumbs down". To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints.
Keywords
Computer Science
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