Fallacies are defective arguments with faulty reasoning. Detecting and classifying them is a
crucial NLP task to prevent misinformation, manipulative claims, and biased decisions …

Argument mining (AM) is the process of automatically extracting arguments, their
components and/or relations amongst arguments and components from text. As the number …

Computational Argumentation studies how human argumentative reasoning can be
approached from a computational viewpoint. Human argumentation is a complex process …

The climate crisis is a salient issue in online discussions, and hypocrisy accusations are a
central rhetorical element in these debates. However, for large-scale text analysis, hypocrisy …

The development of Large Language Models (LLMs) has brought impressive performances
on mitigation strategies against misinformation, such as counterargument generation …

Detecting logical fallacies in texts can help users spot argument flaws, but automating this
detection is not easy. Manually annotating fallacies in large-scale, real-world text data to …

Prior research in computational argumentation has mainly focused on scoring the quality of
arguments, with less attention on explicating logical errors. In this work, we introduce four …

Argument schemes represent stereotypical patterns of reasoning that capture the inferences
from premise (s) to conclusion. Despite their usefulness in argument mining, argument …

This contribution presents a methodology to investigate the soundness of GPT-4
explanations through a combination of fallacy theory and linguistic refinement. It seeks to …

Nowadays, the spread of disinformation poses a major challenge for society. Citizens find
themselves immersed in a complex and data-saturated digital context that hinders their …