Details

Identifying Argumentative Discourse Structures in Persuasive Essays

Author Christian Stab, Iryna Gurevych
Date October 2014
Kind Inproceedings
Editor Alessandro Moschitti, Bo Pang, Walter Daelemans
PublisherAssociation for Computational Linguistics
AddressStroudsburg, PA, USA
Book titleConference on Empirical Methods in Natural Language Processing (EMNLP 2014)
Pages46-56
LocationDoha, Qatar
KeyTUD-CS-2014-0882
Research Areas Ubiquitous Knowledge Processing, UKP_reviewed, UKP_p_WIKULU, UKP_p_WIWEB, UKP_p_DKPro, UKP_s_DKPro_Core, UKP_s_DKPro_Lab, UKP_a_ArMin
Abstract In this paper, we present a novel approach for identifying argumentative discourse structures in persuasive essays. The structure of argumentation consists of several components (i.e. claims and premises) that are connected with argumentative relations. We consider this task in two consecutive steps. First, we identify the components of arguments using multiclass classification. Second, we classify a pair of argument components as either support or non-support for identifying the structure of argumentative discourse. For both tasks, we evaluate several classifiers and propose novel feature sets including structural, lexical, syntactic and contextual features. In our experiments, we obtain a macro F1-score of 0.726 for identifying argument components and 0.722 for argumentative relations.
Website www.ukp.tu-darmstadt.de/data/argumentation-mining/argument-annotated-essays/
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