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Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation

Habernal, Ivan ; Wachsmuth, Henning ; Gurevych, Iryna ; Stein, Benno (2018):
Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation.
In: Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 386-396,
Association for Computational Linguistics, New Orleans, USA, [Conference or Workshop Item]

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Habernal, Ivan ; Wachsmuth, Henning ; Gurevych, Iryna ; Stein, Benno
Title: Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation
Language: English
Book Title: Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Publisher: Association for Computational Linguistics
Uncontrolled Keywords: UKP_a_ArMin;UKP_p_ArguAna
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 1994 Adaptive Preparation of Information from Heterogeneous Sources
Event Location: New Orleans, USA
Date Deposited: 16 Feb 2018 08:59
URL / URN: http://aclweb.org/anthology/N18-1036
Additional Information:

Arguing without committing a fallacy is one of the main requirements of an ideal debate. But even when debating rules are strictly enforced and fallacious arguments punished, arguers often lapse into attacking the opponent by an ad hominem argument. As existing research lacks solid empirical investigation of the typology of ad hominem arguments as well as their potential causes, this paper fills this gap by (1) performing several large-scale annotation studies, (2) experimenting with various neural architectures and validating our working hypotheses, such as controversy or reasonableness, and (3) providing linguistic insights into triggers of ad-hominem using explainable neural network architectures.

Identification Number: TUD-CS-2018-0029
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