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Sentiment Analysis using Latent Structural SVM
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 Title & Authors
Sentiment Analysis using Latent Structural SVM
Yang, Seung-Won; Lee, Changki;
 
 Abstract
In this study, comments on restaurants, movies, and mobile devices, as well as tweet messages regardless of specific domains were analyzed for sentimental information content. We proposed a system for extraction of objects (or aspects) and opinion words from each sentence and the subsequent evaluation. For the sentiment analysis, we conducted a comparative evaluation between the Structural SVM algorithm and the Latent Structural SVM. As a result, the latter showed better performance and was able to extract objects/aspects and opinion words using VP/NP analyzed by the dependency parser tree. Lastly, we also developed and evaluated the sentiment detector model for use in practical services.
 Keywords
sentiment detector;opinion mining;sentiment analysis;Latent Structural SVM;opinion word;
 Language
Korean
 Cited by
 References
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