Abstract
We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently. Combining the constraints across many adjectives, a clustering algorithm separates the adjectives into groups of different orientations, and finally, adjectives are labeled positive or negative. Evaluations on real data and simulation experiments indicate high levels of performance: classification precision is more than 90% for adjectives that occur in a modest number of conjunctions in the corpus.
Keywords
Conjunction (astronomy)Computer scienceTask (project management)Orientation (vector space)Natural language processingArtificial intelligenceCluster analysisRegressionMathematicsStatistics
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Publication Info
- Year
- 1997
- Type
- article
- Pages
- 174-181
- Citations
- 1434
- Access
- Closed
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Cite This
Vasileios Hatzivassiloglou,
Kathleen McKeown
(1997).
Predicting the semantic orientation of adjectives.
Proceedings of the 35th annual meeting on Association for Computational Linguistics -
, 174-181.
https://doi.org/10.3115/976909.979640
Identifiers
- DOI
- 10.3115/976909.979640