Self-training from labeled features for sentiment analysis

Author:

He Yulan,Zhou Deyu

Publisher

Elsevier BV

Subject

Library and Information Sciences,Management Science and Operations Research,Computer Science Applications,Media Technology,Information Systems

Reference33 articles.

1. Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums;Abbasi;ACM Transactions on Information Systems,2008

2. Andreevskaia, A., & Bergler, S. (2008). When specialists and generalists work together: Overcoming domain dependence in sentiment tagging. In Proceedings of the association for computational linguistics and the human language technology conference (ACL-HLT) (pp. 290–298).

3. Argamon, S., Bloom, K., Esuli, A., & Sebastiani, F. (2007). Automatically determining attitude type and force for sentiment analysis. In Proceedings of the 3rd language and technology conference (pp. 218–231).

4. Blitzer, J., Dredze, M., & Pereira, F. (2007). Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In Proceedings of the association for computational linguistics (ACL) (pp. 440–447).

5. Choi, Y., Cardie, C., Riloff, E., & Patwardhan, S. (2005). Identifying sources of opinions with conditional random fields and extraction patterns. In Proceedings of human language technology conference and conference on empirical methods in natural language processing (HLT/EMNLP) (pp. 355–362).

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