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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 Carroll
We 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.

History

Publication status

  • Published

Page range

304-311

Presentation Type

  • paper

Event name

Proceedings of the Third International Joint Conference on Natural Language Processing (IJCNLP)

Event location

Hyderabad, India

Event type

conference

Department affiliated with

  • Informatics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-04-30

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