Extended models and tools for high-performance part-of-speech tagger
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Compilation of a dictionary of japanese functional expressions with hierarchical organization
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
How do negation and modality impact on opinions?
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
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We propose a method for classifying opinions which captures the role of linguistic modalities in the sentence. We use features than simple bag-of-words or opinion-holding predicates. The method is based on a machine learning and utilizes opinion-holding predicates and linguistic modalities as features. Two different detectors help to classify the opinions: the opinion-holding predicate detector and the modality detector. An opinion in the target is first parsed into a dependency structure, and then the opinion-holding predicates and modalities stick onto the leaf nodes of the dependency tree. The whole tree is regarded as input features of the opinion, and it becomes the input of tree kernel support vector machines. We have applied method to opinions in Japanese about television programs, and have confirmed the effectiveness of the method against conventional bag-of-words features, or against simple opinion-holding predicates features