[LVIC-LIMSI]: Using Syntactic Features and Multi-polarity Words for Sentiment Analysis in Twitter
Morgane Marchand, Alexandru Ginsca, Romaric Besançon, Olivier Mesnard · Joint Conference on Lexical and Computational Semantics · 2013
This paper presents the contribution of our team at task 2 of SemEval 2013: Sentiment Analysis in Twitter. We submitted a constrained run for each of the two subtasks. In the Contextual Polarity Disambiguation subtask, we use a sentiment lexicon approach combined with polarity shift detection and tree kernel based classifiers. In the Message Polarity Classification subtask, we focus on the influence of domain information on sentiment classification.