Abstract
In this paper we apply the information state update (ISU) machinery to tracking and understanding the argumentative behaviour of participants in a parliamentary debate in order to predict its outcome. We propose to use the ISU approach to model the arguments of the debaters and the support/attack links between them as part of the formal representations of a participant’s information state. We first consider the identification of claims and evidence relations to their premises as an argument mining task. It is not sufficient, however, to indicate what relations occur without establishing how these relations are created and verified during the interaction. For this purpose the model requires a detailed specification of the creation, maintenance and use of shared beliefs. The ISU model provides procedures for incorporating beliefs and expectations shared between speaker and hearers in the tracking model. To evaluate the content of the tracked information states, we compare them to those of the human ‘concluder’ who wraps up a debate, stating the claims which the majority of the debaters have agreed on.
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Notes
- 1.
Youth Parliaments have been founded in many European countries and all over the world, e.g. in Greece, South Africa, Columbia. The European Youth Parliament is also active since 1987.
- 2.
- 3.
See as example http://www.youtube.com/watch?v=g2Fg-LJHPA4.
- 4.
Here and henceforth Dk stands for Debater k; the subscript is the index of the identified functional segment.
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- 6.
- 7.
- 8.
- 9.
The inter-annotator agreement between three experienced annotators on this task was very high, 0.87 in terms of Cohen’s kappa.
- 10.
Here and henceforth _x.y is the index assigned to the conclusion of an ADU, where x indicates the debater index and y stands for the index of an ADU conclusion.
- 11.
Note we do not distinguish between rebuttals and undercutters in this study.
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- 13.
- 14.
For the sake of simplicity we do not spell out the semantic content of the propositions and leave out evidence links here.
References
Walton, D.N.: Argumentation Schemes for Presumptive Reasoning. Routledge, Abingdon (1996)
Moens, M., Boiy, E., Mochales-Palau, R., Reed, C.: Automatic detection of arguments in legal texts. In: Proceedings of the ICAIL 2007, Stanford, California, pp. 225–230 (2007)
Reed, C., Mochales-Palau, R., Rowe, G., Moens, M.: Language resources for studying argument. In: Proceedings of the LREC 2008, Marrakech, Morocco, pp. 2613–2618 (2008)
Teufel, S.: Argumentative zoning: information extraction from scientific text. Ph.D. thesis, University of Edinburgh (1999)
Toulmin, S.: The Uses of Arguments. Cambridge University Press, Cambridge (1958)
Petukhova, V., Bunt, H.: Incremental recognition and prediction of dialogue acts. In: Bunt, H., Bos, J., Pulman, S. (eds.) Computing Meaning, vol. 4, pp. 235–256. Springer, Dordrecht (2014)
Keizer, S.: Reasoning under uncertainty in natural language dialogue using Bayesian networks. Ph.D. thesis, Twente University Press, The Netherlands (2003)
Lendvai, P., van den Bosch, A., Krahmer, E., Canisius, S.: Memory-based robust interpretation of recognised speech. In: Proceedings of the SPECOM 2004, St. Petersburgh, Russia, pp. 415–422 (2004)
Stolcke, A., Ries, K., Coccaro, K., Shriberg, E., Bates, R., Jurafsky, D., Taylor, P., Martin, R., van Ess-Dykema, C., Meteer, M.: Dialogue act modeling for automatic tagging and recognition of conversational speech. Comput. Linguist. 26(3), 339–373 (2000)
Punyakanok, V., Roth, D.: The use of classifiers in sequential inference. In: NIPS, pp. 995–1001 (2001)
Klein, W.: Argumentation and argument. Zeitschrift für Literaturwissenschaft und Linguistik 10(38/39), 9–56 (1980)
Freeman, J.B.: Argument Structure: Representation and Theory. Argumentation Library, vol. 18. Springer, Berlin (2011)
Peldszus, A., Stede, M.: From argument diagrams to argumentation mining in texts: a survey. Int. J. Cogn. Inf. Natural Intell. (IJCINI) 7(1), 1–31 (2013)
Mann, W., Thompson, S.: Rhetorical Structure Theory: Toward a Functional Theory of Text Organisation. MIT Press, Cambridge (1988)
Sanders, T., Spooren, W., Noordman, L.: Toward a taxonomy of coherence relations. Discourse Process. 15, 1–35 (1992)
Hobbs, J.: On the coherence and structure of discourse. Research report 85–37, CSLI, Stanford (1985)
Asher, N., Lascarides, A.: Logics of Conversation. Cambridge University Press, Cambridge (2003)
Cohen, R.: A computational theory of the function of clue words in argument understanding. In: Proceedings of the COLING-ACL 1984, Standford, pp. 251–258 (1984)
Poesio, M., Traum, D.: Towards an axiomatization of dialogue acts. In: Proceedings of the Twente Workshop on the Formal Semantics and Pragmatics of Dialogues, pp. 207–222 (1998)
Bunt, H.: Information dialogues as communicative action in relation to partner modelling and information processing. In: Taylor, M., Neel, F., Bouwhuis, D. (eds.) The Structure of Multimodal Dialogue, vol. 1, pp. 47–73. Elsevier, North Holland (1989)
ISO: Language resource management - Semantic annotation framework - Part 2: Dialogue acts. ISO 24617–2. ISO Central Secretariat, Geneva (2012)
Sporleder, C., Lascarides, A.: Using automatically labelled examples to classify rhetorical relations: an assessment. Nat. Lang. Eng. 14(03), 369–416 (2008)
Marcu, D.: The rhetorical parsing of natural language texts. In: Proceedings of of Association for Computational Linguistics Annual Conference (ACL), pp. 96–103 (1997)
Hirschberg, J., Litman, D.: Empirical studies on the disambiguation of cue phrases. Comput. Linguist. 25(4), 501–530 (1993)
Sacks, H., Schegloff, E., Jefferson, G.: A simplest systematics for the organization of turn-taking for conversation. Language 50(4), 696–735 (1974)
Grosz, B.J., Sidner, C.L.: Attention, intentions, and the structure of discourse. Comput. Linguist. 12, 175–204 (1986)
Ishimoto, Y., Tsuchiya, T., Koiso, H., Den, Y.: Towards automatic transformation between different transcription conventions: prediction of intonation markers from linguistic and acoustic features. In: Proceedings of the LREC 2014, Reykjavik, Iceland, pp. 311–315 (2014)
Prasad, R., Dinesh, N., Lee, A., Miltsakaki, E., Robaldo, L., Joshi, A., Webber, B.: The penn discourse treebank 2.0. In: Proceedings of the LREC 2008, Marrakech, Maroc, pp. 2961–2968 (2008)
Hovy, E., Maier, E.: Parsimonious of profligate: how many and which discourse structure relations? (1995, unpublished manuscript)
Bos, J.: Towards wide-coverage semantic interpretation. In: Proceedings of the 6th International Conference on Computational Semantics (IWCS-6), pp. 42–53 (2005)
Bunt, H.: Annotations that effectively contribute to semantic interpretation. In: Bunt, H., Bos, J., Pulman, S. (eds.) Computing Meaning, vol. 47, pp. 49–69. Springer, Dordrecht (2014)
Bunt, H.: A context-change semantics for dialogue acts. In: Bunt, H., Bos, J., Pulman, S. (eds.) Computing Meaning, vol. 4, pp. 177–201. Springer, Dordrecht (2014)
Searle, J.R.: Speech Acts. Cambridge University Press, Cambridge (1969)
Fischer, G.: User modeling in human-computer interaction. User Model. User-Adap. Inter. 11, 65–68 (2001)
Bunt, H., Keizer, S., Morante, R.: A computational model of grounding in dialogue. In: Proceedings of SIGDIAL 2007, Antwerp, Belgium, pp. 283–290 (2007)
Florou, E., Konstantopoulos, S., Koukourikos, A., Karampiperis, P.: Argument extraction for supporting public policy formulation. In: Proceedings of the LATECH Workshop, Sofia, Bulgaria (2013)
Acknowledgements
The underlying research project is partly funded by the EU FP7 Metalogue project, under grant agreement number 611073. We are also very thankful to anonymous reviewers for their valuable comments.
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Petukhova, V., Malchanau, A., Bunt, H. (2016). Modelling Argumentative Behaviour in Parliamentary Debates: Data Collection, Analysis and Test Case. In: Baldoni, M., et al. Principles and Practice of Multi-Agent Systems. CMNA IWEC IWEC 2015 2015 2014. Lecture Notes in Computer Science(), vol 9935. Springer, Cham. https://doi.org/10.1007/978-3-319-46218-9_3
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