Compatibility of Arguments from Different Functional Groups in Scientific Texts
Pimenov Ivan Sergeevich
Novosibirsk State University
Submitted: 06.10.2022
Abstract. The study aims to determine the compatibility of arguments from different functional groups in a collection of scientific texts. The study is novel in that it develops a functional classification of argumentation schemes and identifies the features of using arguments from different functional groups in the collection of Russian-language scientific texts (it is the first time that such an analysis of functional compatibility of arguments has been carried out both for texts of the scientific genre and for texts in Russian). Based on a comparative analysis of the semantics of arguments and the functional features of their use, a classifi-cation of argumentation schemes has been developed differentiating four methods of proof (from authority, from practical value, through elaboration or causal analysis). The use of arguments from four groups has been investigated using a set of 1030 reasoning sequences extracted from expertly annotated scientific papers on linguistics and computer technology. It has been shown that the analysed papers are characterised by an active combination of arguments from different functional groups with their uneven positional arrangement in some sequences, depending on the emphasis in the proof. The work includes the following parts: argumentation modelling, a functional comparison of argumentation schemes, presentation of reasoning through functional blocks, a compatibility analysis of such arguments.
Key words and phrases: автоматический анализ аргументации, моделирование аргументации, модели рассуждения, научные тексты, automatic argumentation analysis, argumentation modelling, reasoning models, scientific texts
Open the whole article in PDF format. Free PDF-files viewer can be downloaded here.
References:
Kotel'nikov E. V. Izvlechenie argumentatsii iz tekstov i problema otsutstviya russkoyazychnykh tekstovykh korpusov // Advanced Science. 2018. № 3 (11).
Sidorova E. A., Akhmadeeva I. R., Zagorul'ko Yu. A., Seryi A. S., Shestakov V. K. Platforma dlya issledovaniya argumentatsii v nauchno-populyarnom diskurse // Ontologiya proektirovaniya. 2020. T. 10. № 4 (38).
Al-Khatib K., Wachsmuth H., Hagen M., Stein B. Patterns of Argumentation Strategies across Topics // Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (Copenhagen, September 7-11, 2017). Copenhagen, 2017.
Amossy R. Argumentation in Discourse. A Socio-Discursive Approach to Arguments // Informal Logic. 2009. Vol. 29 (3).
Barbieri E., Aggujaro S., Molteni F., Luzzatti C. Does Argument Structure Complexity Affect Reading? A Case Study of an Italian Agrammatic Patient with Deep Dyslexia // Applied Psycholinguistics. 2015. Vol. 36. Iss. 3.
Kononenko I., Sidorova E., Akhmadeeva I.Comparative Analysis of Rhetorical and Argumentative Structures in the Study of Popular Science Discourse // International Conference on Computational Linguistics and Intellectual Technologies “Dialogue”. Moscow, 2020.
Lawrence J., Reed C. Argument Mining: A Survey // Computational Linguistics. 2019. Vol. 45. No. 4.
Pimenov I., Salomatina N., Timofeeva M. The Quantitative Evaluation of the Pathos to Ethos Ratio in Scientific Texts // Proceedings of the 2022 IEEE 23rd International Conference of Young Professionals in Electron Devices and Materials (EDM). Altai, 2022.
Rahwan I., Reed C. The Argument Interchange Format // Argumentation in Artificial Intelligence / ed. by I. Rahwan, G. Simari. Dordrecht - Heidelberg - L. - N. Y.: Springer, 2009.
Walton D., Reed C., Macagno F. Argumentation Schemes. N. Y.: Cambridge University Press, 2008.
Zagorulko Yu. A., Domanov O. A., Sery A. S., Sidorova E. A., Borovikova O. I. Analysis of the Persuasiveness of Argumentation in Popular Science Texts // Artificial Intelligence, Proceedings of the 18th Russian Conference RCAI. Moscow, 2020.