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Extracting opinions, opinion holders, and topics expressed in online news media text (2006)
| Content Provider | CiteSeerX |
|---|---|
| Author | Kim, Soo-Min Hovy, Eduard |
| Description | Proceedings of ACL the Workshop on Sentiment and Subjectivity in Text |
| Abstract | This paper presents a method for identi-fying an opinion with its holder and topic, given a sentence from online news media texts. We introduce an approach of exploiting the semantic structure of a sentence, anchored to an opinion bearing verb or adjective. This method uses se-mantic role labeling as an intermediate step to label an opinion holder and topic using data from FrameNet. We decom-pose our task into three phases: identify-ing an opinion-bearing word, labeling semantic roles related to the word in the sentence, and then finding the holder and the topic of the opinion word among the labeled semantic roles. For a broader coverage, we also employ a clustering technique to predict the most probable frame for a word which is not defined in FrameNet. Our experimental results show that our system performs significantly better than the baseline. 1 |
| File Format | |
| Publisher Date | 2006-01-01 |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Proceeding Conference Proceedings |
