Paper: BOUNCE: Sentiment Classification in Twitter using Rich Feature Sets

ACL ID S13-2093
Title BOUNCE: Sentiment Classification in Twitter using Rich Feature Sets
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

The widespread use of Twitter makes it very interesting to determine the opinions and the sentiments expressed by its users. The short- ness of the length and the highly informal na- ture of tweets render it very difficult to auto- matically detect such information. This paper reports the results to a challenge, set forth by SemEval-2013 Task 2, to determine the posi- tive, neutral, or negative sentiments of tweets. Two systems are explained: System A for de- termining the sentiment of a phrase within a tweet and System B for determining the senti- ment of a tweet. Both approaches rely on rich feature sets, which are explained in detail.