Paper: Kea: Expression-level Sentiment Analysis from Twitter Data

ACL ID S13-2088
Title Kea: Expression-level Sentiment Analysis from Twitter Data
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes an expression-level senti- ment detection system that participated in the subtask A of SemEval-2013 Task 2: Senti- ment Analysis in Twitter. Our system uses a supervised approach to learn the features from the training data to classify expressions in new tweets as positive, negative or neutral. The proposed approach helps to understand the rel- evant features that contribute most in this clas- sification task.