Why are You Taking this Stance? Identifying and Classifying Reasons in Ideological Debates
Kazi Saidul Hasan and Vincent Ng.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 751-762, 2014.
Click here for the PostScript or PDF
version.
The talk slides are available here.
Abstract
Recent years have seen a surge of interest in stance classification in online
debates. Oftentimes, however, it is important to determine not only the stance
expressed by an author in her debate posts, but also the reasons behind her
supporting or opposing the issue under debate. We therefore
examine the new task of reason classification in this paper. Given the close interplay between stance classification and reason classification, we design computational models for examining how automatically computed stance information can be profitably exploited for reason classification.
Experiments on our reason-annotated corpus of ideological debate posts from four domains demonstrate that sophisticated models of stances and reasons can indeed yield more accurate reason and stance classification results than their simpler counterparts.
Dataset
The dataset used in this paper is available from
this page.
BibTeX entry
@InProceedings{Hasan+Ng:14b,
author = {Hasan, Kazi Saidul and Vincent Ng},
title = {Why are You Taking this Stance? Identifying and Classifying Reasons in Ideological Debates},
booktitle = {Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing},
pages = {751--762},
year = 2014}
