Paper: Portable Features for Classifying Emotional Text

ACL ID N12-1071
Title Portable Features for Classifying Emotional Text
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012
Authors

Are word-level affect lexicons useful in de- tecting emotions at sentence level? Some prior research finds no gain over and above what is obtained with ngram features?arguably the most widely used features in text classifica- tion. Here, we experiment with two very dif- ferent emotion lexicons and show that even in supervised settings, an affect lexicon can pro- vide significant gains. We further show that while ngram features tend to be accurate, they are often unsuitable for use in new domains. On the other hand, affect lexicon features tend to generalize and produce better results than ngrams when applied to a new domain.