Paper: SAIL: A hybrid approach to sentiment analysis

ACL ID S13-2072
Title SAIL: A hybrid approach to sentiment analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes our submission for Se- mEval2013 Task 2: Sentiment Analysis in Twitter. For the limited data condition we use a lexicon-based model. The model uses an af- fective lexicon automatically generated from a very large corpus of raw web data. Statistics are calculated over the word and bigram af- fective ratings and used as features of a Naive Bayes tree model. For the unconstrained data scenario we combine the lexicon-based model with a classifier built on maximum entropy language models and trained on a large exter- nal dataset. The two models are fused at the posterior level to produce a final output. The approach proved successful, reaching rank- ings of 9th and 4th in the twitter sentiment analysis constrained and unconstrained sce- nario respectively, despite using onl...