Recommended or Not Recommended? Review Classification through Opinion Extraction
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TL;DR
The proposed method first mines the product features and relevant opinions, and then determines the overall sentiment orientation of the review based on the polarity and strength of these opinions.
Abstract
With the rapid growth of web 2.0, online product reviews generated by users are becoming increasingly useful for customers to make purchase decisions. In this paper, we focus on the problem of classifying user reviews as recommended the product or not. The proposed method first mines the product features and relevant opinions, and then determines the overall sentiment orientation of the review based on the polarity and strength of these opinions. The evaluation results show the effectiveness of our proposed method in product feature mining and review classification.