FBK: Sentiment Analysis in Twitter with Tweetsted
Md. Faisal Mahbub Chowdhury, Marco Guerini, Sara Tonelli, Alberto Lavelli · Joint Conference on Lexical and Computational Semantics · 2013
This paper presents the Tweetsted system implemented for the SemEval 2013 task on Sentiment Analysis in Twitter. In particular, we participated in Task B on Message Polarity Classification in the Constrained setting. The approach is based on the exploitation of various resources such as SentiWordNet and LIWC. Official results show that our approach yields a F-score of 0.5976 for Twitter messages (11th out of 35) and a F-score of 0.5487 for SMS messages (8th out of 28 participants).