Argument Analytics

John Lawrence, Rory Duthie, Katarzyna Budzynska, Chris Reed

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

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Abstract

Rapid growth in the area of argument mining has resulted in an ever increasing volume of analysed argument data. Being able to store information about arguments people make in favour or against different opinions, decisions and actions is a highly valuable resource, yet extremely challenging for sense-making. How, for example, can an analyst quickly check whether in a corpus of citizen dialogue people tend to rather agree or disagree with new policies proposed by the department of transportation; how can she get an insight into the interactions typical of this specific dialogical context; how can the general public easily see which presidential candidate is currently winning the debate by being able to successfully defend his arguments? In this paper, we propose Argument Analytics – a suite of techniques which provide interpretation of, and insight into, large-scale argument data for both specialist and general audiences.
Original languageEnglish
Title of host publicationComputational Models of Argument
Subtitle of host publicationProceedings from the Sixth International Conference on Computational Models of Argument (COMMA)
EditorsPietro Baroni, Thomas F. Gordon, Tatjana Scheffler, Manfred Stede
Place of PublicationNetherlands
PublisherIOS Press
Pages371-378
Number of pages8
Volume287
ISBN (Electronic)9781614996866
ISBN (Print)9781614996859
DOIs
Publication statusPublished - 2016
EventThe 6th International Conference on Computational Models of Argument - University of Potsdam, Potsdam, Germany
Duration: 13 Sep 201616 Sep 2016
http://www.ling.uni-potsdam.de/comma2016/

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Volume287
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

ConferenceThe 6th International Conference on Computational Models of Argument
CountryGermany
CityPotsdam
Period13/09/1616/09/16
Internet address

Fingerprint

General Public
Interaction
Resources
Sensemaking

Keywords

  • Argument Interchange Format
  • corpus resources
  • argument visualisation

Cite this

Lawrence, J., Duthie, R., Budzynska, K., & Reed, C. (2016). Argument Analytics. In P. Baroni, T. F. Gordon, T. Scheffler, & M. Stede (Eds.), Computational Models of Argument: Proceedings from the Sixth International Conference on Computational Models of Argument (COMMA) (Vol. 287, pp. 371-378). (Frontiers in Artificial Intelligence and Applications; Vol. 287). Netherlands: IOS Press. https://doi.org/10.3233/978-1-61499-686-6-371
Lawrence, John ; Duthie, Rory ; Budzynska, Katarzyna ; Reed, Chris. / Argument Analytics. Computational Models of Argument: Proceedings from the Sixth International Conference on Computational Models of Argument (COMMA). editor / Pietro Baroni ; Thomas F. Gordon ; Tatjana Scheffler ; Manfred Stede. Vol. 287 Netherlands : IOS Press, 2016. pp. 371-378 (Frontiers in Artificial Intelligence and Applications).
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Lawrence, J, Duthie, R, Budzynska, K & Reed, C 2016, Argument Analytics. in P Baroni, TF Gordon, T Scheffler & M Stede (eds), Computational Models of Argument: Proceedings from the Sixth International Conference on Computational Models of Argument (COMMA). vol. 287, Frontiers in Artificial Intelligence and Applications, vol. 287, IOS Press, Netherlands, pp. 371-378, The 6th International Conference on Computational Models of Argument, Potsdam, Germany, 13/09/16. https://doi.org/10.3233/978-1-61499-686-6-371

Argument Analytics. / Lawrence, John; Duthie, Rory; Budzynska, Katarzyna; Reed, Chris.

Computational Models of Argument: Proceedings from the Sixth International Conference on Computational Models of Argument (COMMA). ed. / Pietro Baroni; Thomas F. Gordon; Tatjana Scheffler; Manfred Stede. Vol. 287 Netherlands : IOS Press, 2016. p. 371-378 (Frontiers in Artificial Intelligence and Applications; Vol. 287).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

TY - CHAP

T1 - Argument Analytics

AU - Lawrence, John

AU - Duthie, Rory

AU - Budzynska, Katarzyna

AU - Reed, Chris

N1 - We would like to acknowledge that the work reported in this paper has been supported in part by EPSRC in the UK under grants EP/M506497/1, EP/N014871/1 and EP/K037293/1.

PY - 2016

Y1 - 2016

N2 - Rapid growth in the area of argument mining has resulted in an ever increasing volume of analysed argument data. Being able to store information about arguments people make in favour or against different opinions, decisions and actions is a highly valuable resource, yet extremely challenging for sense-making. How, for example, can an analyst quickly check whether in a corpus of citizen dialogue people tend to rather agree or disagree with new policies proposed by the department of transportation; how can she get an insight into the interactions typical of this specific dialogical context; how can the general public easily see which presidential candidate is currently winning the debate by being able to successfully defend his arguments? In this paper, we propose Argument Analytics – a suite of techniques which provide interpretation of, and insight into, large-scale argument data for both specialist and general audiences.

AB - Rapid growth in the area of argument mining has resulted in an ever increasing volume of analysed argument data. Being able to store information about arguments people make in favour or against different opinions, decisions and actions is a highly valuable resource, yet extremely challenging for sense-making. How, for example, can an analyst quickly check whether in a corpus of citizen dialogue people tend to rather agree or disagree with new policies proposed by the department of transportation; how can she get an insight into the interactions typical of this specific dialogical context; how can the general public easily see which presidential candidate is currently winning the debate by being able to successfully defend his arguments? In this paper, we propose Argument Analytics – a suite of techniques which provide interpretation of, and insight into, large-scale argument data for both specialist and general audiences.

KW - Argument Interchange Format

KW - corpus resources

KW - argument visualisation

U2 - 10.3233/978-1-61499-686-6-371

DO - 10.3233/978-1-61499-686-6-371

M3 - Chapter (peer-reviewed)

SN - 9781614996859

VL - 287

T3 - Frontiers in Artificial Intelligence and Applications

SP - 371

EP - 378

BT - Computational Models of Argument

A2 - Baroni, Pietro

A2 - Gordon, Thomas F.

A2 - Scheffler, Tatjana

A2 - Stede, Manfred

PB - IOS Press

CY - Netherlands

ER -

Lawrence J, Duthie R, Budzynska K, Reed C. Argument Analytics. In Baroni P, Gordon TF, Scheffler T, Stede M, editors, Computational Models of Argument: Proceedings from the Sixth International Conference on Computational Models of Argument (COMMA). Vol. 287. Netherlands: IOS Press. 2016. p. 371-378. (Frontiers in Artificial Intelligence and Applications). https://doi.org/10.3233/978-1-61499-686-6-371