TY - JOUR

T1 - On Developing a Web Resource to Study Argumentation in Popular Science Discourse

AU - Daria, Ilina

AU - Irina, Kononenko

AU - Elena, Sidorova

N1 - Ilina D. On Developing a Web Resource to Study Argumentation in Popular Science Discourse / D. Ilina, I. Kononenko, E. Sidorova // Компьютерная лингвистика и интеллектуальные технологии : По материалам ежегодной международной конференции «Диалог». – Вып. 20. – М.: РГГУ, 2021. – P. 318–327. DOI 10.28995/2075-7182-2021-20-318-327

PY - 2021

Y1 - 2021

N2 - This paper discusses the experience of developing a web resource intended to study argumentation in popular science discourse. Such type of argumentation is, on the one hand, the main mean of achieving a communicative goal and, on the other hand, often not expressed in explicit form. The web resource is built around a corpus of 2256 articles, distributed over 13 subcorpora. The annotation model, which is based on the ontology of argumentation and D. Walton's argumentation schemes for presumptive reasoning, underlies the argument annotation of the corpus. The distinctive features of the argument annotation model are the introduction of weighting characteristics into text markup through assessing the persuasiveness of the argumentation, as well as highlighting argumentative indicators visually. The paper considers a scenario of argument annotation of texts, which allows constructing an argumentative graph based on the typical reasoning schemes. The scenario includes a number of procedures that enable the annotator to check the quality of the text markup and assess the persuasiveness of the argumentation. The authors have annotated 162 texts, using the developed web resource, and as a result, identified the most frequent schemes of argumentation (Example Inference, Cause to Effect Inference, Expert Opinion Inference), as well as described some specific indicators of frequent schemes. Based on the above-mentioned outcomes, the authors listed the indicators of the most frequent schemes of argumentation and made some recommendations for annotators about identifying the main thesis.

AB - This paper discusses the experience of developing a web resource intended to study argumentation in popular science discourse. Such type of argumentation is, on the one hand, the main mean of achieving a communicative goal and, on the other hand, often not expressed in explicit form. The web resource is built around a corpus of 2256 articles, distributed over 13 subcorpora. The annotation model, which is based on the ontology of argumentation and D. Walton's argumentation schemes for presumptive reasoning, underlies the argument annotation of the corpus. The distinctive features of the argument annotation model are the introduction of weighting characteristics into text markup through assessing the persuasiveness of the argumentation, as well as highlighting argumentative indicators visually. The paper considers a scenario of argument annotation of texts, which allows constructing an argumentative graph based on the typical reasoning schemes. The scenario includes a number of procedures that enable the annotator to check the quality of the text markup and assess the persuasiveness of the argumentation. The authors have annotated 162 texts, using the developed web resource, and as a result, identified the most frequent schemes of argumentation (Example Inference, Cause to Effect Inference, Expert Opinion Inference), as well as described some specific indicators of frequent schemes. Based on the above-mentioned outcomes, the authors listed the indicators of the most frequent schemes of argumentation and made some recommendations for annotators about identifying the main thesis.

KW - Annotation scenario

KW - Argument annotation of text

KW - Argumentation indicator

KW - Popular science discourse

KW - Text corpus

KW - Annotation scenario

KW - Argument annotation of text

KW - Argumentation indicator

KW - Popular science discourse

KW - Text corpus

UR - http://www.scopus.com/inward/record.url?scp=85124404738&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/2c31f12b-5521-3107-af24-3923bde98d19/

U2 - 10.28995/2075-7182-2021-20-318-327

DO - 10.28995/2075-7182-2021-20-318-327

M3 - Conference article

AN - SCOPUS:85124404738

VL - 2021-June

SP - 318

EP - 327

JO - Компьютерная лингвистика и интеллектуальные технологии

JF - Компьютерная лингвистика и интеллектуальные технологии

SN - 2221-7932

IS - 20

T2 - 2021 Annual International Conference on Computational Linguistics and Intellectual Technologies, Dialogue 2021

Y2 - 16 June 2021 through 19 June 2021

ER -