UWB at SemEval-2016 Task 6: Stance Detection
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) (2016)
Abstract
This paper describes our system participating in the SemEval 2016 task: Detecting stance in Tweets. The goal was to identify whether the author of a tweet is in favor of the given target or against. Our approach is based on a maximum entropy classifier, which uses surface-level, sentiment and domain-specific features. We participated in both the supervised and weakly supervised subtasks and received promising results for most of the targets.
Authors
BibTex
@InProceedings{krejzl-steinberger:2016:SemEval, author = {Krejzl, Peter and Steinberger, Josef}, title = {UWB at SemEval-2016 Task 6: Stance Detection}, booktitle = {Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)}, month = {June}, year = {2016}, address = {San Diego, California}, publisher = {Association for Computational Linguistics}, pages = {408--412}, url = {http://www.aclweb.org/anthology/S16-1066} }
