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Analyzing the structure of argumentative discourse

Author:

Robin CohenAuthors Info & Claims

Computational Linguistics, Volume 13, Issue 1-2

Pages 11 - 24

Published: 01 January 1987 Publication History

Abstract

Consider a discourse situation where the speaker tries to convince the hearer of a particular point of view. The first task for the hearer is to understand what it is the speaker wants him to believe--to analyze the structure of the argument being presented, before judging credibility and eventually responding.This paper describes a model for the analysis of arguments that includes:• a theory of expected coherent structure which is used to limit analysis to the reconstruction of particular transmission forms;• a theory of linguistic clues which assigns a functional interpretation to special words and phrases used by the speaker to indicate the structure of the argument;• a theory of evidence relationships which includes the demand for pragmatic analysis to accommodate beliefs not currently held.The implications of this particular design for dialogue analysis in general are thus:• structure is an important feature to extract in a representation to control the processing;• linguistic constructions can be assigned useful interpretations;• pragmatic analysis is crucial in cases where the participants differ in beliefs.

References

[1]

Archbold, A. 1976 A Study of Some Argument Forms in a Persuasion Dialogue. ISI internal document, Marina del Rey, California.

[2]

Archbold, A. and Hobbs, J. 1980 Notes on "The Analysis of Evaluative Argumentation in Text": A Report on On-Going Work. SRI unpublished draft, Menlo Park, California.

[3]

Birnbaum, L.; Flowers, M.; and McGuire, R. 1980 Towards an AI Model of Argumentation. Proceedings of American Association for Artificial Intelligence (AAAI) Conference: 313--315.

[4]

Cohen, P. 1978 On Knowing What to Say: Planning Speech Acts. Technical Report No. 118, Computer Science Department, University of Toronto, Toronto, Ontario, Canada.

[5]

Cohen, R. 1980 Understanding Arguments. Proceedings of Canadian Society for Computational Studies of Intelligence (CSCSI) Conference: 272--279.

[6]

Cohen, R. 1981 Investigation of Processing Strategies for the Structural Analysis of Arguments. Proceedings of the Association for Computational Linguistics (ACL) Conference: 71--75.

Digital Library

[7]

Cohen, R. 1983 A Computational Model for the Analysis of Arguments. Ph.D. thesis, Technical Report No. 151, Computer Systems Research Group, University of Toronto, Toronto, Ontario, Canada.

Digital Library

[8]

Cohen, R. 1984a A Theory of Discourse Coherence for Argument Understanding. Proceedings of Canadian Society for Computational Studies of lntelligence (CSCSl) Conference: 6--10.

[9]

Cohen, R. 1984b A Computational Theory of the Function of Clue Words in Argument Understanding. Proceedings of 10th International Conference on Computational Linguistics (COLING 84): 251--258.

Digital Library

[10]

Cohen, R. 1985 The Need for Pragmatics in Natural Language Understanding. Proceedings of CSCSI-sponsored Theoretical Advances in Natural Language Understanding Conference.

[11]

Gazdar, G. 1979 Pragmatics: lmplicature, Presupposition and Logical Form. Academic Press, New York, New York.

[12]

Geva, E. 1981 Flowcharting Expository Texts and Reading Comprehension. Paper presented al Annual Meeting of American Educational Research Association.

[13]

Grosz, B. 1977 The Representation and Use of Focus in Dialogue Understanding. SRI Technical Note No. 151, Menlo Park, California.

[14]

Grosz, B. and Sidner, C. 1986 The Structures of Discourse Structure. Report No. 6097. Bolt, Beranek and Newman (BBN) Cambridge. Massachusetts. (also Report No. CSLI-85-39; Attention, Intentions, and the Structure of Discourse, Computational Linguistics 12(3): 175--204.

Digital Library

[15]

Hobbs, J. 1976 A Computational Approach to Discourse Analysis. Research Report No. 76-2. City University of New York Department of Computer, New York, New York.

[16]

Labov, W. and Fanshel, D. 1977 Therapeutic Discourse. Academic Press, New York, New York.

[17]

McCarty, L. and Sridharan, N.S. 1981 A Computational Theory of Legal Argumentation. Research Report LRP-TR-13, Rutgers University Lab for Computer Science, New Brunswick, New Jersey.

[18]

McGuirc, R., Birnbaum, L. and Flowers, M. 1981 Opportunistic Processing in Arguments. Proceedings of the International Joint Conference on Artificial lntelligence.bf one;(lJCAl) Conference: 58--60.

[19]

Pollack, M. 1986 A Model of Plan Inference that Distinguishes Between the Beliefs of Actors and Observers. Proceedings of the Association for Computational Linguistics (ACL) Conference: 207--214.

Digital Library

[20]

Quirk, R. et. al. 1972 A Grammar of Contemporary English. Longmans Co., London, England.

[21]

Reichman, R. 1981 Plain Speaking: A Theory and Grammar of Spontaneous Discourse. Report No. 4681, Bolt, Beranek and Newman (BBN), Cambridge, Massachusetts.

[22]

Sadock, J. 1977 Modus Brevis: The Truncated Argument. Papers from the 13th Regional Meeting, Chicago Linguistics Society: 545--554.

[23]

Sidner, C. 1979 Towards a Computational Theory of Definite Anaphora Comprehension in English Discourse. AI Lab Report TR-537, Massacusetts Institute of Technology (MIT), Cambridge, Massachusetts.

Digital Library

[24]

Smedley, T. 1986 An Implementation of a Computational Model for the Analysis of Arguments: An Introduction to the First Attempt. Research Report CS-86-26, University of Waterloo Department of Computer Science, Waterloo, Ontario, Canada.

[25]

Weiner, J. 1979 BLAH, A System which Explains Its Reasoning. Technical Report TR 79-14, University of New Hampshire Computer Science Department, Durham, New Hampshire.

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Sachan MDubey AHovy EMitchell TRoth DXing E(2020)Discourse in MultimediaComputational Linguistics10.1162/coli_a_0036045:4(627-665)Online publication date: 1-Jan-2020
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Analyzing the structure of argumentative discourse
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cover image Computational Linguistics

Computational Linguistics Volume 13, Issue 1-2

January-June 1987

149 pages

ISSN:0891-2017

EISSN:1530-9312

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MIT Press

Cambridge, MA, United States

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Published: 01 January 1987

Published in COLI Volume 13, Issue 1-2

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Cited By

Hsiao FYen AHuang HChen H(2022)Modeling Inter Round Attack of Online Debaters for Winner PredictionProceedings of the ACM Web Conference 202210.1145/3485447.3512006(2860-2869)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3485447.3512006
Sachan MDubey AHovy EMitchell TRoth DXing E(2020)Discourse in MultimediaComputational Linguistics10.1162/coli_a_0036045:4(627-665)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1162/coli_a_00360
Schaekermann MBeaton GHabib MLim ALarson KLaw E(2019)Understanding Expert Disagreement in Medical Data Analysis through Structured AdjudicationProceedings of the ACM on Human-Computer Interaction10.1145/33591783:CSCW(1-23)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3359178
Schaekermann MBeaton GHabib MLim ALarson KLaw E(2019)Capturing Expert Arguments from Medical Adjudication Discussions in a Machine-readable FormatCompanion Proceedings of The 2019 World Wide Web Conference10.1145/3308560.3317085(1131-1137)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308560.3317085
Hastings PHughes SBritt ABlaum DWallace P(2014)Toward Automatic Inference of Causal Structure in Student Essays12th International Conference on Intelligent Tutoring Systems - Volume 847410.1007/978-3-319-07221-0_33(266-271)Online publication date: 5-Jun-2014
https://dl.acm.org/doi/10.1007/978-3-319-07221-0_33
Georgila KArtstein RNazarian ARushforth MTraum DSycara KMoore JTraum DChai JPassonneau R(2011)An annotation scheme for cross-cultural argumentation and persuasion dialoguesProceedings of the SIGDIAL 2011 Conference10.5555/2132890.2132920(272-278)Online publication date: 17-Jun-2011
https://dl.acm.org/doi/10.5555/2132890.2132920
Feng VHirst GLin D(2011)Classifying arguments by schemeProceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 110.5555/2002472.2002597(987-996)Online publication date: 19-Jun-2011
https://dl.acm.org/doi/10.5555/2002472.2002597
Mochales RMoens M(2011)Argumentation miningArtificial Intelligence and Law10.1007/s10506-010-9104-x19:1(1-22)Online publication date: 1-Mar-2011
https://dl.acm.org/doi/10.1007/s10506-010-9104-x
Mahalakshmi GGeetha T(2010)Multi-robot learning using non-deterministic argument gamesInternational Journal of Autonomous and Adaptive Communications Systems10.1504/IJAACS.2010.0355483:4(439-463)Online publication date: 1-Sep-2010
https://dl.acm.org/doi/10.1504/IJAACS.2010.035548
Palau RMoens M(2009)Argumentation miningProceedings of the 12th International Conference on Artificial Intelligence and Law10.1145/1568234.1568246(98-107)Online publication date: 8-Jun-2009
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