Stance detection in online discussions
WIKT & DaZ 2016 (2016)
Abstract
This paper describes our system created to detect stance in online discussions. The goal is to identify whether the author of a comment 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. The system was originally developed to detect stance in English tweets. We adapted it to process Czech news commentaries.
Authors
BibTex
@inproceedings{dataaznalosti2016, title = {Stance detection in online discussions}, author = {Peter Krejzl and Barbora Hourov{\'a} and Josef Steinberger}, booktitle = {WIKT \& DaZ 2016}, editor = {M{\'a}ria Bielikov{\'a} and Ivan Srba}, year = {2016}, publisher = {Vydate{\v{l}}stvo STU, Vazovova 5, Bratislava, Slovakia}, venue = {Smolenice, Slovakia}, pages = {211-214}, url = "https://wikt-daz2016.fiit.stuba.sk/wp-content/uploads/2016/11/WIKT-DaZ-2016_Proceedings.pdf", isbn = {978-80-227-4619-9} }
