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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Sentiment Classification: A Combination of PMI, SentiWordNet and Fuzzy Function
verfasst von : Anh-Dung Vo, Cheol-Young Ock
Erschienen in: Computational Collective Intelligence. Technologies and Applications
Verlag: Springer Berlin Heidelberg
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Discerning a consensus opinion about a product or service is difficult due to the many opinions on the web. To overcome this problem, sentiment classification has been applied as an important approach for evaluation in sentiment mining. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques such as unsupervised and machine learning methods. This paper proposes an unsupervised method for classifying the polarity of reviews using a combination of methods including PMI, SentiWordNet and adjusting the phrase score in the case of modification. The experiment results show that the proposed system achieves accuracy ranging from 69.36% for movie reviews to 80.16% for automotive reviews.