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Effects of adjective orientation and gradability on sentence subjectivity
Open accessAbstract
Subjectivity is a pragmatic, sentence-level feature that has important implications for text processing applications such as information extraction and information retrieval. We study the effects of dynamic adjectives, semantically oriented adjectives, and gradable adjectives on a simple subjectivity classifier, and establish that they are strong predictors of subjectivity. A novel trainable method that statistically combines two indicators of gradability is presented and evaluated, complementing existing automatic techniques for assigning orientation labels.
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Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
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Thumbs up?: sentiment classification using machine learning techniques
Pang, B., Lee, L., & Vaithyanathan, S. (2002) · Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02 · doi:10.3115/1118693.1118704 · Cited by 7,024
Ensemble of feature sets and classification algorithms for sentiment classification
Xia, R., Zong, C., & Li, S. (2011) · Information Sciences · doi:10.1016/j.ins.2010.11.023 · Cited by 583
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(2012) · Open Research Online (The Open University) · Cited by 163
Metadata
- Authors
- Hatzivassiloglou, V., & Wiebe, J. M.
- Venue
- Proceedings of the 18th conference on Computational linguistics -
- Published
- 2000
- Volume
- 1
- Pages
- 299-305
- ISSN
- 1525-2477 (ISSN-L)
- OpenAlex
- W1998442272
- Cited by
- 671
- References
- 2
- FWCI
- 3.38
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Hatzivassiloglou, V., & Wiebe, J. M. (2000). Effects of adjective orientation and gradability on sentence subjectivity. Proceedings of the 18th conference on Computational linguistics -. https://doi.org/10.3115/990820.990864
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