Theme Aspect Argumentation Model for Handling Fallacies
Ryuta Arisaka, Ryoma Nakai, Yusuke Kawamoto, Takayuki Ito

TL;DR
This paper introduces a novel context-aware argumentation model called the theme aspect argumentation model, which uses formal constraints to identify fallacies with explainability and formal rigor.
Contribution
It proposes a new formal, explainable approach to fallacy detection using the theme aspect argumentation model, enhancing interpretability and accuracy.
Findings
Formal constraints effectively identify fallacies.
The model supports both rhetorical and semantic analysis.
Decidability and complexity of the constraints are analyzed.
Abstract
From daily discussions to marketing ads to political statements, information manipulation is rife. It is increasingly more important that we have the right set of tools to defend ourselves from manipulative rhetoric, or fallacies. Suitable techniques to automatically identify fallacies are being investigated in natural language processing research. However, a fallacy in one context may not be a fallacy in another context, so there is also a need to explain how and why it has come to be judged a fallacy. For the explainable fallacy identification, we present a novel approach to characterising fallacies through formal constraints, as a viable alternative to more traditional fallacy classifications by informal criteria. To achieve this objective, we introduce a novel context-aware argumentation model, the theme aspect argumentation model, which can do both: the modelling of a given…
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Advanced Text Analysis Techniques
