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A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
Open accessAbstract
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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Metadata
- Authors
- Pang, B., & Lee, L.
- Venue
- Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04
- Published
- 2004
- Pages
- 271-es
- OpenAlex
- W2114524997
- Cited by
- 3,301
- References
- 1
- FWCI
- 32.09
- Type
- conference paper
- Language
- en
- Open access
- bronze
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