Paper: Stance Classification using Dialogic Properties of Persuasion

ACL ID N12-1072
Title Stance Classification using Dialogic Properties of Persuasion
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012
Authors

Public debate functions as a forum for both expressing and forming opinions, an impor- tant aspect of public life. We present results for automatically classifying posts in online debate as to the position, or STANCE that the speaker takes on an issue, such as Pro or Con. We show that representing the dialogic struc- ture of the debates in terms of agreement rela- tions between speakers, greatly improves per- formance for stance classification, over mod- els that operate on post content and parent- post context alone.