Revisiting computational models of argument schemes: Classification, annotation, comparison

Jacky Visser; John Lawrence; Jean Wagemans; Chris Reed

doi:10.3233/978-1-61499-906-5-313

Revisiting computational models of argument schemes: Classification, annotation, comparison

Jacky Visser (Lead / Corresponding author), John Lawrence, Jean Wagemans, Chris Reed

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

17 Citations (Scopus)

423 Downloads (Pure)

Abstract

In this paper, we present an in-depth comparative analysis of two classifications of argument schemes: Walton's typology and Wagemans' Periodic Table of Arguments. We describe annotation guidelines for each classification and apply these to a corpus of arguments from the 2016 US presidential debates. In so doing, we achieve substantial inter-annotator agreement, and produce what, to the best of our knowledge, are the two largest and most reliably annotated corpora of argument schemes in dialogical argumentation publicly available. In describing the creation and comparison of these corpora, we discuss the strengths of each, with an eye towards both computational modelling and argument mining.

Original language	English
Title of host publication	Computational Models of Argument - Proceedings of COMMA 2018
Editors	Sanjay Modgil, Katarzyna Budzynska, John Lawrence, Katarzyna Budzynska
Publisher	IOS Press
Pages	313-324
Number of pages	12
Volume	305
ISBN (Print)	9781614999058
DOIs	https://doi.org/10.3233/978-1-61499-906-5-313
Publication status	Published - 2018
Event	7th International Conference on Computational Models of Argument, COMMA 2018 - Warsaw, Poland Duration: 12 Sept 2018 → 14 Sept 2018

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	305
ISSN (Print)	0922-6389

Conference

Conference	7th International Conference on Computational Models of Argument, COMMA 2018
Country/Territory	Poland
City	Warsaw
Period	12/09/18 → 14/09/18

Keywords

Annotation
Argument mining
Argument schemes
Classification
Corpus

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.3233/978-1-61499-906-5-313Licence: CC BY-NC

Final Published VersionFinal published version, 265 KBLicence: CC BY-NC

Cite this

Visser, J., Lawrence, J., Wagemans, J., & Reed, C. (2018). Revisiting computational models of argument schemes: Classification, annotation, comparison. In S. Modgil, K. Budzynska, J. Lawrence, & K. Budzynska (Eds.), Computational Models of Argument - Proceedings of COMMA 2018 (Vol. 305, pp. 313-324). (Frontiers in Artificial Intelligence and Applications; Vol. 305). IOS Press. https://doi.org/10.3233/978-1-61499-906-5-313

Visser, Jacky ; Lawrence, John ; Wagemans, Jean et al. / Revisiting computational models of argument schemes : Classification, annotation, comparison. Computational Models of Argument - Proceedings of COMMA 2018. editor / Sanjay Modgil ; Katarzyna Budzynska ; John Lawrence ; Katarzyna Budzynska. Vol. 305 IOS Press, 2018. pp. 313-324 (Frontiers in Artificial Intelligence and Applications).

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title = "Revisiting computational models of argument schemes: Classification, annotation, comparison",

abstract = "In this paper, we present an in-depth comparative analysis of two classifications of argument schemes: Walton's typology and Wagemans' Periodic Table of Arguments. We describe annotation guidelines for each classification and apply these to a corpus of arguments from the 2016 US presidential debates. In so doing, we achieve substantial inter-annotator agreement, and produce what, to the best of our knowledge, are the two largest and most reliably annotated corpora of argument schemes in dialogical argumentation publicly available. In describing the creation and comparison of these corpora, we discuss the strengths of each, with an eye towards both computational modelling and argument mining.",

keywords = "Annotation, Argument mining, Argument schemes, Classification, Corpus",

author = "Jacky Visser and John Lawrence and Jean Wagemans and Chris Reed",

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note = "7th International Conference on Computational Models of Argument, COMMA 2018 ; Conference date: 12-09-2018 Through 14-09-2018",

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Visser, J , Lawrence, J, Wagemans, J & Reed, C 2018, Revisiting computational models of argument schemes: Classification, annotation, comparison. in S Modgil, K Budzynska, J Lawrence & K Budzynska (eds), Computational Models of Argument - Proceedings of COMMA 2018. vol. 305, Frontiers in Artificial Intelligence and Applications, vol. 305, IOS Press, pp. 313-324, 7th International Conference on Computational Models of Argument, COMMA 2018, Warsaw, Poland, 12/09/18. https://doi.org/10.3233/978-1-61499-906-5-313

Revisiting computational models of argument schemes: Classification, annotation, comparison. / Visser, Jacky (Lead / Corresponding author); Lawrence, John; Wagemans, Jean et al.
Computational Models of Argument - Proceedings of COMMA 2018. ed. / Sanjay Modgil; Katarzyna Budzynska; John Lawrence; Katarzyna Budzynska. Vol. 305 IOS Press, 2018. p. 313-324 (Frontiers in Artificial Intelligence and Applications; Vol. 305).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Revisiting computational models of argument schemes

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AB - In this paper, we present an in-depth comparative analysis of two classifications of argument schemes: Walton's typology and Wagemans' Periodic Table of Arguments. We describe annotation guidelines for each classification and apply these to a corpus of arguments from the 2016 US presidential debates. In so doing, we achieve substantial inter-annotator agreement, and produce what, to the best of our knowledge, are the two largest and most reliably annotated corpora of argument schemes in dialogical argumentation publicly available. In describing the creation and comparison of these corpora, we discuss the strengths of each, with an eye towards both computational modelling and argument mining.

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KW - Argument mining

KW - Argument schemes

KW - Classification

KW - Corpus

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Visser J , Lawrence J, Wagemans J, Reed C. Revisiting computational models of argument schemes: Classification, annotation, comparison. In Modgil S, Budzynska K, Lawrence J, Budzynska K, editors, Computational Models of Argument - Proceedings of COMMA 2018. Vol. 305. IOS Press. 2018. p. 313-324. (Frontiers in Artificial Intelligence and Applications). doi: 10.3233/978-1-61499-906-5-313

Revisiting computational models of argument schemes: Classification, annotation, comparison

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Argument Mining

Cite this

Revisiting computational models of argument schemes: Classification, annotation, comparison

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

Argument Mining

Cite this