Abstract
Sentiment analysis is an example of polarity learning. Most research on learning to identify sentiment ignores "neutral" examples and instead performs training and testing using only examples of significant polarity. We show that it is crucial to use neutral examples in learning polarity for a variety of reasons and show how neutral examples help us obtain superior classification results in two sentiment analysis test-beds.
| Original language | English |
|---|---|
| Pages (from-to) | 1616-1617 |
| Number of pages | 2 |
| Journal | IJCAI International Joint Conference on Artificial Intelligence |
| State | Published - 2005 |
| Event | 19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom Duration: 30 Jul 2005 → 5 Aug 2005 |