TY - GEN

T1 - The Quantitative Evaluation of the Pathos to Ethos Ratio in Scientific Texts

AU - Pimenov, Ivan S.

AU - Salomatina, Natalia V.

AU - Timofeeva, Mariya K.

N1 - Funding Information: The research was conducted within the framework of the state contract of the Sobolev Institute of Mathematics (projects no. FWNF-2022-0015 and FWNF-2022-0011). Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - In this paper we present the annotation-based argumentation analysis of scientific texts with the aim of quantitatively evaluating their persuasiveness in terms of two infrequently studied persuasion modes: ethos and pathos. The expert annotation of texts is performed manually through the use of web-tools for visualizing argumentative statements and reasoning schemes, along with representing the argumentation structure of a text in form of a directed graph. In these graphs, argumentative statements and connecting arguments (reasoning models) are correspondingly denoted by information nodes and scheme nodes. We describe a method to evaluate the argumentation in a text for ethos and pathos distinctly, by analyzing both the content of information nodes (premises and conclusions) and the functionality of corresponding reasoning models. For evaluating information nodes, we have constructed two dictionaries of argumentation markers that are represented by lexical-syntactical patterns and respectively identify ethos and pathos in collection texts. Quantitative values are calculated for 30 annotated texts of the collection. We employ these values to group these texts into several sets based on the proportion of pathos and ethos.

AB - In this paper we present the annotation-based argumentation analysis of scientific texts with the aim of quantitatively evaluating their persuasiveness in terms of two infrequently studied persuasion modes: ethos and pathos. The expert annotation of texts is performed manually through the use of web-tools for visualizing argumentative statements and reasoning schemes, along with representing the argumentation structure of a text in form of a directed graph. In these graphs, argumentative statements and connecting arguments (reasoning models) are correspondingly denoted by information nodes and scheme nodes. We describe a method to evaluate the argumentation in a text for ethos and pathos distinctly, by analyzing both the content of information nodes (premises and conclusions) and the functionality of corresponding reasoning models. For evaluating information nodes, we have constructed two dictionaries of argumentation markers that are represented by lexical-syntactical patterns and respectively identify ethos and pathos in collection texts. Quantitative values are calculated for 30 annotated texts of the collection. We employ these values to group these texts into several sets based on the proportion of pathos and ethos.

KW - argumentation

KW - ethos and pathos

KW - persuasion modes

KW - persuasiveness of texts

KW - scientific texts

UR - http://www.scopus.com/inward/record.url?scp=85137325151&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/0b5f85e6-43a0-3f78-86b6-c32f95b768ea/

U2 - 10.1109/EDM55285.2022.9855111

DO - 10.1109/EDM55285.2022.9855111

M3 - Conference contribution

AN - SCOPUS:85137325151

SN - 9781665498043

T3 - International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM

SP - 312

EP - 317

BT - Proceedings of the 2022 IEEE 23rd International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

PB - IEEE Computer Society

T2 - 23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

Y2 - 30 June 2022 through 4 July 2022

ER -