Paper: The Impact of Z_score on Twitter Sentiment Analysis

ACL ID S14-2113
Title The Impact of Z_score on Twitter Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

Twitter has become more and more an im- portant resource of user-generated data. Sen- timent Analysis in Twitter is interesting for many applications and objectives. In this pa- per, we propose to exploit some features which can be useful for this task; the main contribution is the use of Z-scores as features for sentiment classification in addition to pre-polarity and POS tags features. Our ex- periments have been evaluated using the test data provided by SemEval 2013 and 2014. The evaluation demonstrates that Z_scores features can significantly improve the predic- tion performance.