DRACS: Diachronic Representation of Argument Construction Styles

TY - GEN

T1 - DRACS

T2 - 28th European Conference on Artificial Intelligence

AU - Kostiuk, Yevhen

AU - Lawrence, John

AU - Reed, Chris

N1 - Conference code: 28th

PY - 2025/10/21

Y1 - 2025/10/21

N2 - In computational argument mining, the final constructed argument graph is usually the center of attention, with researchers analyzing its structure and developing methods to extract valuable insights from it. In this paper, we argue that analyzing only the final argument graph is not enough. We demonstrate that the same argument graphs do not imply the same argument construction styles (ways of populating them), which are an important abstract argumentation concept. Therefore, both final structure and the construction style should be considered when analyzing arguments. To address the analysis of argument construction styles, we present the DRACS: Diachronic Representation of Argument Construction Styles framework to capture argument construction style features and enable their analysis alongside the graph structures. We evaluate our methodology on three distinct datasets of pre-defined similar and differing construction styles: the AIF-labeled corpora UNSC and US2016, as well as a custom corpus of synthetic tree-based argument graphs. We apply our method to highlight similarities and differences of argument construction styles on US2016 datasets. Our findings suggest that even if the final argument graphs display a high degree of similarity, their construction styles could differ significantly.

AB - In computational argument mining, the final constructed argument graph is usually the center of attention, with researchers analyzing its structure and developing methods to extract valuable insights from it. In this paper, we argue that analyzing only the final argument graph is not enough. We demonstrate that the same argument graphs do not imply the same argument construction styles (ways of populating them), which are an important abstract argumentation concept. Therefore, both final structure and the construction style should be considered when analyzing arguments. To address the analysis of argument construction styles, we present the DRACS: Diachronic Representation of Argument Construction Styles framework to capture argument construction style features and enable their analysis alongside the graph structures. We evaluate our methodology on three distinct datasets of pre-defined similar and differing construction styles: the AIF-labeled corpora UNSC and US2016, as well as a custom corpus of synthetic tree-based argument graphs. We apply our method to highlight similarities and differences of argument construction styles on US2016 datasets. Our findings suggest that even if the final argument graphs display a high degree of similarity, their construction styles could differ significantly.

UR - https://www.scopus.com/pages/publications/105024460160

U2 - 10.3233/FAIA250991

DO - 10.3233/FAIA250991

M3 - Conference contribution

T3 - Frontiers in Artificial Intelligence and Applications

SP - 1647

EP - 1654

BT - ECAI 2025 - 28th European Conference on Artificial Intelligence, including 14th Conference on Prestigious Applications of Intelligent Systems, PAIS 2025 - Proceedings

A2 - Lynce, Inês

A2 - Murano, Nello

A2 - Vallati, Mauro

A2 - Villata, Serena

A2 - Chesani, Federico

A2 - Milano, Michela

A2 - Omicini, Andrea

A2 - Dastani, Mehdi

PB - IOS Press

Y2 - 25 October 2025 through 30 November 2025

ER -