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

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. Publication info: Proceedings of the ACL, 2004.

• Type: Conference
• Year: 2004
• Where: ACL
• Authors: Bo Pang, Lillian Lee
• Keywords: ACL 2004, ACL 2007, Sentiment Analysis, Sentiment Polarity, Thumbs Down