Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Computational Linguistics
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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
Identifying and analyzing judgment opinions
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Toward opinion summarization: linking the sources
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
| Hi-index | 0.00 |
Opinion holder identification research is important for discriminating between opinions that are viewed from different perspectives. We propose a new opinion holder identification method that is based on a differentiation between the author and authority viewpoints in opinionated sentences. In our method, the author- and authority-opinionated sentences were extracted, respectively, by utilizing the different features because their writing styles were different. Although the researchers have not focused on it, this differentiation is important for correctly identifying opinion holders. We describe our participation in the NTCIR-6 Opinion Analysis Pilot Task by focusing on the opinion holder identification results in Japanese and English. The evaluation results showed that our system performed fairly well with respect to Japanese documents, and postsubmission analysis has revealed that improvements could be made with respect to English documents as well.