Argotario: Computational Argumentation Meets Serious Games

Abstract

An important skill in critical thinking and argumentation is the ability to spot and recognize fallacies. Fallacious arguments, omnipresent in argumentative discourse, can be deceptive, manipulative, or simply leading to 'wrong moves' in a discussion. Despite their importance, argumentation scholars and NLP researchers with focus on argumentation quality have not yet investigated fallacies empirically. The nonexistence of resources dealing with fallacious argumentation calls for scalable approaches to data acquisition and annotation, for which the serious games methodology offers an appealing, yet unexplored, alternative. We present Argotario, a serious game that deals with fallacies in everyday argumentation. Argotario is a multilingual, open-source, platform-independent application with strong educational aspects, accessible at www.argotario.net.

Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detection

“…Habernal et al (2018b) presented a corpus of Web forum discussions with instances of ad hominem fallacy. Habernal et al (2017Habernal et al ( , 2018a introduced Argotario, a game to educate people to recognize and create fallacies, a by-product of which is a corpus with 1.3k arguments annotated with five fallacies such as ad hominem, red herring and irrelevant authority, which directly relate to propaganda.…”

“…Unlike (Habernal et al, 2017(Habernal et al, , 2018a, our corpus uses 18 techniques annotated on the same set of news articles. Moreover, our annotations aim at identifying the minimal fragments related to a technique instead of flagging entire arguments.…”

Crowdsourcing Complex Associations among Words by Means of A Game

“…Lessons learned from such an experience clearly show that games need to be attractive, fun, and interesting to be successful in a long-term perspective [16]. The aspect of interestingness is particularly difficult to preserve if a game needs specific training [17] or it involves (potentially long) free-text entries produced by the user [18]. Text adventure games provide an example of attractive environments that can naturally lead to building useful language resources [19].…”

Neural Architectures for Fine-Grained Propaganda Detection in News

“…Prior works (Rashkin et al, 2017;Habernal et al, 2017; in detecting propaganda have focused primarily at document level, typically labeling all articles from a propagandistic news outlet as propaganda and thus, often non-propagandistic articles from the outlet are mislabeled. To this end, Da San focuses on analyzing the use of propaganda and detecting specific propagandistic techniques in news articles at sentence and fragment level, respectively and thus, promotes explainable AI.…”