FBM: Combining lexicon-based ML and heuristics for Social Media Polarities

Abstract

This paper describes the system implemented by Fundació Barcelona Media (FBM) for classifying the polarity of opinion expressions in tweets and SMSs, and which is supported by a UIMA pipeline for rich linguistic and sentiment annotations. FBM participated in the SEMEVAL 2013 Task 2 on polarity classification. It ranked 5th in Task A (constrained track) using an ensemble system combining ML algorithms with dictionary-based heuristics, and 7th (Task B, constrained) using an SVM classifier with features derived from the linguistic annotations and some heuristics. 1