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Sentiment classification of online Cantonese reviews by supervised machine learning approaches

Sentiment classification of online Cantonese reviews by supervised machine learning approaches Cantonese is an important Chinese dialect spoken in some regions of Southern China. Local online users often represent their opinions and experiences with written Cantonese on the web. With two supervised machine learning approaches, this paper conducts a series of experiments to explore appropriate methods for automatic sentiment classification in the very noisy domain of online Cantonese-written reviews. Findings indicate that the support vector machine classifier based on a Mandarin Chinese word segmentation tool performs surprisingly well. The accuracy, precision and recall respectively for positive and negative reviews all reach above 85% when the training corpus contains 5,000 or more reviews. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Web Engineering and Technology Inderscience Publishers

Sentiment classification of online Cantonese reviews by supervised machine learning approaches

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1476-1289
eISSN
1741-9212
DOI
10.1504/IJWET.2009.032254
Publisher site
See Article on Publisher Site

Abstract

Cantonese is an important Chinese dialect spoken in some regions of Southern China. Local online users often represent their opinions and experiences with written Cantonese on the web. With two supervised machine learning approaches, this paper conducts a series of experiments to explore appropriate methods for automatic sentiment classification in the very noisy domain of online Cantonese-written reviews. Findings indicate that the support vector machine classifier based on a Mandarin Chinese word segmentation tool performs surprisingly well. The accuracy, precision and recall respectively for positive and negative reviews all reach above 85% when the training corpus contains 5,000 or more reviews.

Journal

International Journal of Web Engineering and Technology – Inderscience Publishers

Published: Jan 1, 2009

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