Paper: KUNLPLab:Sentiment Analysis on Twitter Data

ACL ID S14-2067
Title KUNLPLab:Sentiment Analysis on Twitter Data
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper presents the system submitted by KUNLPLab for SemEval-2014 Task9 - Subtask B: Message Polarity on Twitter data. Lexicon features and bag-of-words features are mainly used to represent the datasets. We trained a logistic regression classifier and got an accuracy of 6% in- crease from the baseline feature represen- tation. The effect of pre-processing on the classifier?s accuracy is also discussed in this work.