The importance of neutral examples for learning sentiment

  • Moshe Koppel ,
  • Jonathan Schler

Computational Intelligence | , Vol 22: pp. 100-116

Most research on learning to identify sentiment ignores “neutral” examples, learning only from examples of significant (positive or negative) polarity. We show that it is crucial to use neutral examples in learning polarity for a variety of reasons. Learning from negative and positive examples alone will not permit accurate classification of neutral examples. Moreover, the use of neutral training examples in learning facilitates better distinction between positive and negative examples.