Paper: Unsupervised Classification of Sentiment and Objectivity in Chinese Text

ACL ID I08-1040
Title Unsupervised Classification of Sentiment and Objectivity in Chinese Text
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

We address the problem of sentiment and objectivity classification of product re- views in Chinese. Our approach is distinct- ive in that it treats both positive / negative sentiment and subjectivity / objectivity not as distinct classes but rather as a con- tinuum; we arguethatthis is desirablefrom the perspective of would-be customers who read the reviews. We use novel unsuper- vised techniques, including a one-word 'seed' vocabulary and iterative retraining for sentiment processing, and a criterion of 'sentiment density' for determining the ex- tent to which a document is opinionated. The classifier achieves up to 87% F-meas- ureforsentimentpolaritydetection.