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

ACL ID P04-1035
Title A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based On Minimum Cuts
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004
Authors

Sentiment analysis seeks to identify the view- point(s) underlying a text span; an example appli- cation is classifying a movie review as “thumbs up” or “thumbs down”. To determine this sentiment po- larity, 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.