Paper: nlp.cs.aueb.gr: Two Stage Sentiment Analysis

ACL ID S13-2094
Title nlp.cs.aueb.gr: Two Stage Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes the systems with which we participated in the task Sentiment Analysis in Twitter of SEMEVAL 2013 and specifically the Message Polarity Classification. We used a 2-stage pipeline approach employing a lin- ear SVM classifier at each stage and several features including BOW features, POS based features and lexicon based features. We have also experimented with Naive Bayes classi- fiers trained with BOW features.