On the Visualisation of Argumentation Graphs to Support Text Interpretation

TL;DR

This study investigates how visual argumentation graphs (AGs) enhance the interpretation of complex texts compared to traditional reading, showing AGs improve user experience and support critical analysis, especially with unfamiliar topics.

Contribution

It demonstrates that argumentation graphs improve user engagement and critical interpretation, particularly for unfamiliar topics, offering a novel visualization approach in NLP argumentation analysis.

Findings

AGs outperform text in user experience metrics

Participants preferred AGs despite similar critical interpretation outcomes

AGs encourage more critical questioning with unfamiliar topics

Abstract

The recent evolution in Natural Language Processing (NLP) methods, in particular in the field of argumentation mining, has the potential to transform the way we interact with text, supporting the interpretation and analysis of complex discourse and debates. Can a graphic visualisation of complex argumentation enable a more critical interpretation of the arguments? This study focuses on analysing the impact of argumentation graphs (AGs) compared with regular texts for supporting argument interpretation. We found that AGs outperformed the extrinsic metrics throughout most UEQ scales as well as the NASA-TLX workload in all the terms but not in temporal or physical demand. The AG model was liked by a more significant number of participants, despite the fact that both the text-based and AG models yielded comparable outcomes in the critical interpretation in terms of working memory and altering participants decisions. The interpretation process involves reference to argumentation schemes (linked to critical questions (CQs)) in AGs. Interestingly, we found that the participants chose more CQs (using argument schemes in AGs) when they were less familiar with the argument topics, making AG schemes on some scales (relatively) supportive of the interpretation process. Therefore, AGs were considered to deliver a more critical approach to argument interpretation, especially with unfamiliar topics. Based on the 25 participants conducted in this study, it appears that AG has demonstrated an overall positive effect on the argument interpretation process.