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        <title>Recognizing Insufficiently Supported Arguments in Argumentative Essays</title>
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    <abstract>In this paper, we propose a new task for assessing the quality of natural language arguments. The premises of a well-reasoned argument should provide enough evidence for accepting or rejecting its claim. Although this criterion, known as sufficiency, is widely adopted in argumentation theory, there are no empirical studies on its applicability to real arguments. In this work, we show that human annotators substantially agree on the sufficiency criterion and introduce a novel annotated corpus. Furthermore, we experiment with feature-rich SVMs and Convolutional Neural Networks and achieve 84% accuracy for automatically identifying insufficiently supported arguments. The final corpus as well as the annotation guideline are freely available for encouraging future research on argument quality.</abstract>
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%0 Conference Proceedings
%T Recognizing Insufficiently Supported Arguments in Argumentative Essays
%A Stab, Christian
%A Gurevych, Iryna
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F stab-gurevych-2017-recognizing
%X In this paper, we propose a new task for assessing the quality of natural language arguments. The premises of a well-reasoned argument should provide enough evidence for accepting or rejecting its claim. Although this criterion, known as sufficiency, is widely adopted in argumentation theory, there are no empirical studies on its applicability to real arguments. In this work, we show that human annotators substantially agree on the sufficiency criterion and introduce a novel annotated corpus. Furthermore, we experiment with feature-rich SVMs and Convolutional Neural Networks and achieve 84% accuracy for automatically identifying insufficiently supported arguments. The final corpus as well as the annotation guideline are freely available for encouraging future research on argument quality.
%U https://aclanthology.org/E17-1092/
%P 980-990

Markdown (Informal)

[Recognizing Insufficiently Supported Arguments in Argumentative Essays](https://aclanthology.org/E17-1092/) (Stab & Gurevych, EACL 2017)

• Recognizing Insufficiently Supported Arguments in Argumentative Essays (Stab & Gurevych, EACL 2017)

ACL

• Christian Stab and Iryna Gurevych. 2017. Recognizing Insufficiently Supported Arguments in Argumentative Essays. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 980–990, Valencia, Spain. Association for Computational Linguistics.