A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts

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A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts (2004)

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by Bo Pang , Lillian Lee

Venue:	PROCEEDINGS OF THE ACL
Citations:	617 - 7 self

BibTeX

@MISC{Pang04asentimental,
    author = {Bo Pang and Lillian Lee},
    title = {A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts},
    year = {2004}
}

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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.

Keyphrases

minimum cut sentiment analysis using subjectivity summarization sentimental education sentiment polarity cross-sentence contextual constraint publication info movie review subjective portion sentiment analysis text span text-categorization technique novel machine-learning method example application efficient technique

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