Opinion Analysis based on Lexical Clues and their Expansion
نویسندگان
چکیده
The challenge of an automatic opinion analysis has been the focus of attention in recent years in many domains such as online product review. Especially, in online news articles opinion analysis has good prospects, since newspaper is the most powerful media to disseminate people’s opinions. We introduce a lexical information based approach to this task by exploiting lexical information, based on the quantitative analysis of opinions in the news articles. The method comprises semi-supervised subjectivity classification, gloss based sentiment classification, and rule based opinion holder finder. The method we present is remarkable since numbers of lexical clues we discovered were effective to this task. The experimental results show that our system achieves 45% of performance to extract opinionated sentences and 35% of performance to identify opinion holders.
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