Sentiment classification of drug reviews using a rule-based linguistic approach

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Abstract

Clause-level sentiment classification algorithm is developed and applied to drug reviews on a discussion forum. The algorithm adopts a pure linguistic approach of computing the sentiment of a clause from the prior sentiment scores assigned to individual words, taking into consideration the grammatical dependency structure of the clause using the sentiment analysis rules. MetaMap, a medical resource tool, is used to identify various disease terms in the review documents to utilize domain knowledge for sentiment classification. Experiment results with 1,000 clauses show the effectiveness of the proposed approach, and it performed significantly better than baseline machine learning approaches. Various challenging issues were identified through error analysis, and we will continue improving our linguistic algorithm. © 2012 Springer-Verlag.

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Na, J. C., Kyaing, W. Y. M., Khoo, C. S. G., Foo, S., Chang, Y. K., & Theng, Y. L. (2012). Sentiment classification of drug reviews using a rule-based linguistic approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7634 LNCS, pp. 189–198). https://doi.org/10.1007/978-3-642-34752-8_25

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