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 linear 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 classifiers trained with BOW features.
['Prodromos Malakasiotis', 'Rafael - Michael Karampatsis', 'Konstantina Makrynioti', 'John Pavlopoulos']
nlp.cs.aueb.gr: Two Stage Sentiment Analysis