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Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences
Open accessAbstract
Opinion question answering is a challenging task for natural language processing. In this paper, we discuss a necessary component for an opinion question answering system: separating opinions from fact, at both the document and sentence level. We present a Bayesian classifier for discriminating between documents with a preponderance of opinions such as editorials from regular news stories, and describe three unsupervised, statistical techniques for the significantly harder task of detecting opinions at the sentence level. We also present a first model for classifying opinion sentences as positive or negative in terms of the main perspective being expressed in the opinion. Results from a large collection of news stories and a human evaluation of 400 sentences are reported, indicating that we achieve very high performance in document classification (upwards of 97% precision and recall), and respectable performance in detecting opinions and classifying them at the sentence level as positive, negative, or neutral (up to 91% accuracy).
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Cited by
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Techniques and applications for sentiment analysis
Feldman, R. (2013) · Communications of the ACM · doi:10.1145/2436256.2436274 · Cited by 1,489
Movie review mining and summarization
Zhuang, L., Jing, F., & Zhu, X.-Y. (2006) · Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06 · doi:10.1145/1183614.1183625 · Cited by 894
Sentiment analysis using product review data
Fang, X., & Zhan, J. (2015) · Journal of Big Data · doi:10.1186/s40537-015-0015-2 · Cited by 788
Wiebe, J., Wilson, T., Bruce, R., Bell, M., & Martin, M. (2004) · Computational Linguistics · doi:10.1162/0891201041850885 · Cited by 748
Metadata
- Authors
- Yu, H., & Hatzivassiloglou, V.
- Venue
- Proceedings of the 2003 conference on Empirical methods in natural language processing -
- Published
- 2003
- Volume
- 10
- Pages
- 129-136
- OpenAlex
- W2080558111
- Cited by
- 1,053
- References
- 0
- FWCI
- 18.90
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Yu, H., & Hatzivassiloglou, V. (2003). Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. Proceedings of the 2003 conference on Empirical methods in natural language processing -. https://doi.org/10.3115/1119355.1119372
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