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A Sentimental Education: Sentiment Analysis using Subjectivity Summarization based on Minimum Cuts

, and . Proceedings of ACL-04, 42nd Meeting of the Association for Computational Linguistics, page 271--278. Barcelona, ES, Association for Computational Linguistics, (2004)

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.

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