Comparative Experiments on Sentiment Classification for Online Product Reviews
- Hang Cui ,
- Vibhu Mittal ,
- Mayur Datar
Proceedings of AAAI-06, the 21st National Conference on Artificial Intelligence |
Published by AAAI Press
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.