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 argumentation as it is expressed (rhetorical modelling); and a deeper semantic analysis of the rhetorical argumentation model. By identifying fallacies with formal constraints, it becomes possible to tell whether a fallacy lurks in the modelled rhetoric with a formal rigour. We present core formal constraints for the theme aspect argumentation model and then more formal constraints that improve its fallacy identification capability. We show and prove the consequences of these formal constraints. We then analyse the computational complexities of deciding the satisfiability of the constraints.

翻译：从日常讨论到营销广告再到政治声明，信息操纵现象无处不在。拥有合适的工具来抵御操纵性修辞（即谬误）正变得愈发重要。自然语言处理研究领域正在探索自动识别谬误的适用技术。然而，某个语境中的谬误在另一语境中可能并非谬误，因此还需要解释其被判定为谬误的方式与原因。针对可解释的谬误识别，我们提出了一种通过形式化约束刻画谬误的新方法，作为传统非正式谬误分类标准的可行替代方案。为实现这一目标，我们引入了新颖的上下文感知论证模型——主题方面论证模型，该模型兼具双重功能：对给定论证进行表达层面的建模（修辞建模），以及对修辞论证模型进行深层的语义分析。通过形式约束识别谬误，我们能够以形式化的严谨性判断建模修辞中是否隐藏谬误。我们首先提出主题方面论证模型的核心形式约束，随后给出增强其谬误识别能力的补充形式约束，并证明这些约束的有效性及其推论。最后分析了判定约束可满足性的计算复杂度。