Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Identifying sources of opinions with conditional random fields and extraction patterns
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Mining opinion features in customer reviews
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Topic identification for fine-grained opinion analysis
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
| Hi-index | 0.00 |
In this paper, we propose to identify opinion holders and targets with dependency parser in Chinese news texts, i.e. to identify opinion holders by means of reporting verbs and to identify opinion targets by considering both opinion holders and opinion-bearing words. The experiments with NTCIR-7 MOAT's Chinese test data show that our approach provides better performance than the baselines and most systems reported at NTCIR-7.