Comparative Experiments on Sentiment Classification for Online Product Reviews

Hang Cui, Vibhu Mittal, Mayur Datar

Evaluating text fragments for positive and negative subjective expressions and their strength can be important in applications such as single- or multi- document summarization, document ranking, data mining, etc. This paper looks at a simplified version of the problem: classifying online product reviews into positive and negative classes. We discuss a series of experiments with different machine learning algorithms in order to experimentally evaluate various trade-offs, using approximately 100K product reviews from the web.

Subjects: 12. Machine Learning and Discovery; 13. Natural Language Processing


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