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Unsupervised classification of sentiment and objectivity in Chinese text
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posted on 2023-06-08, 11:22 authored by T Zagibalov, John CarrollWe address the problem of sentiment and objectivity classification of product reviews in Chinese. Our approach is distinctive in that it treats both positive / negative sentiment and subjectivity / objectivity not as distinct classes but rather as a continuum; we argue that this is desirable from the perspective of would-be customers who read the reviews. We use novel unsupervised techniques, including a one-word 'seed' vocabulary and iterative retraining for sentiment processing, and a criterion of 'sentiment density' for determining the extent to which a document is opinionated. The classifier achieves up to 87% F-measure for sentiment polarity detection.
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Publication status
- Published
Page range
304-311Presentation Type
- paper
Event name
Proceedings of the Third International Joint Conference on Natural Language Processing (IJCNLP)Event location
Hyderabad, IndiaEvent type
conferenceDepartment affiliated with
- Informatics Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-04-30Usage metrics
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