Comparative experiments on sentiment classification for online product reviews
Published 16 July 2006
Hang Cui, Vibhu O. Mittal, Mayur Datar
Citations318
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TL;DR
A series of experiments with different machine learning algorithms are discussed in order to experimentally evaluate various trade-offs, using approximately 100K product reviews from the web.
Abstract
Evaluating text fragments for positive and negative sub-jective expressions and their strength can be important in applications such as single- or multi- document sum-marization, document ranking, data mining, etc. This paper looks at a simplified version of the problem: clas-sifying online product reviews into positive and nega-tive classes. We discuss a series of experiments with different machine learning algorithms in order to ex-perimentally evaluate various trade-offs, using approxi-mately 100K product reviews from the web.
Keywords
Computer Science
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