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Argumentation in Text: Discourse Structure Matters

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Computational Linguistics and Intelligent Text Processing (CICLing 2018)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13396))

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Abstract

We address the problem of argument detection by investigating discourse and communicative text structure. A formal graph-based structure called communicative discourse tree (CDT) is used. It consists of a discourse tree (DT) with additional labels on edges, which stand for verbs. These verbs represent communicative actions. Discourse trees are based on rhetoric relations, extracted from a text according to Rhetoric Structure Theory. The problem is tackled as a binary classification task, where the positive class corresponds to texts with arguments and the negative class corresponds to texts with no argumentation. The feature engineering for the classification task is conducted, deciding which discourse and communicative features are better associated with argumentation. New Intense Argumentation dataset is built and described. Mixed dataset including different types of argumentation and different text genres is collected. Evaluation on this mixed dataset is provided.

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Notes

  1. 1.

    https://theranos.com/news/posts/wall-street-journal-letter-to-the-editor.

  2. 2.

    http://www.wsj.com/articles/theranos-has-struggled-with-blood-tests.

  3. 3.

    https://www.ukp.tu-darmstadt.de/fileadmin/user_upload/Group.../EACL2017-Stab.pdf.

  4. 4.

    https://nlds.soe.ucsc.edu/iac2.

  5. 5.

    https://nlds.soe.ucsc.edu/factfeel.

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Acknowledgments

This article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5-100’. It was supported by the RFBR grants 16-29-12982, 16-01-00583.

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Authors and Affiliations

  1. Oracle Inc., Redwood Shores, CA, USA

    Boris Galitsky

  2. National Research University Higher School of Economics, Moscow, Russia

    Dmitry Ilvovsky

  3. Institute for Systems Analysis, Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow, Russia

    Dina Pisarevskaya

Authors
  1. Boris Galitsky
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  2. Dmitry Ilvovsky
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  3. Dina Pisarevskaya
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Correspondence to Dmitry Ilvovsky .

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Editors and Affiliations

  1. Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

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Galitsky, B., Ilvovsky, D., Pisarevskaya, D. (2023). Argumentation in Text: Discourse Structure Matters. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2018. Lecture Notes in Computer Science, vol 13396. Springer, Cham. https://doi.org/10.1007/978-3-031-23793-5_7

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  • DOI: https://doi.org/10.1007/978-3-031-23793-5_7

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