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

ACL ID S13-2080
Title FBM: Combining lexicon-based ML and heuristics for Social Media Polarities
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

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