Comparative Experiments on Sentiment Classification for Online Product Reviews

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.

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Hang Cui, Vibhu O. Mittal, Mayur Datar
• Keywords: AAAI 2006, Document Summarization, Intelligent Agents, Negative Subjective Expressions, Product Reviews