mlsanityData to 7 Oct 2026

Argotario: Computational Argumentation Meets Serious Games

arXiv 1707.06002 ↗First posted 19 Jul 2017cs.CLcited by 29

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Abstract (arXiv)

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.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2017.

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Citing papers per year: 2021: 5; 2022: 2; 2023: 7; 2024: 6; 2025: 5; 2026: 4.

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  1. 2021SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Imagescited by 49
  2. 2021Detecting Propaganda Techniques in Memescited by 43
  3. 2023Multitask Instruction-based Prompting for Fallacy Recognitioncited by 22
  4. 2024Can GPT-4 Identify Propaganda? Annotation and Detection of Propaganda Spans in News Articlescited by 21
  5. 2023ArAIEval Shared Task: Persuasion Techniques and Disinformation Detection in Arabic Textcited by 19
  6. 2022Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabiccited by 18
  7. 2021Interpretable Propaganda Detection in News Articlescited by 16
  8. 2024Missci: Reconstructing Fallacies in Misrepresented Sciencecited by 14
  9. 2021The Spread of Propaganda by Coordinated Communities on Social Mediacited by 10
  10. 2024Are LLMs Good Zero-Shot Fallacy Classifiers?cited by 10
  11. 2024CoCoLoFa: A Dataset of News Comments with Common Logical Fallacies Written by LLM-Assisted Crowdscited by 8
  12. 2025MemeIntel: Explainable Detection of Propagandistic and Hateful Memescited by 8
17 more
  1. 2025Fine-grained Fallacy Detection with Human Label Variationcited by 6
  2. 2021A Second Pandemic? Analysis of Fake News About COVID-19 Vaccines in Qatarcited by 5
  3. 2023QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection using Multilingual Modelscited by 5
  4. 2023Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognitioncited by 5
  5. 2024ArMeme: Propagandistic Content in Arabic Memescited by 5
  6. 2025Towards a Perspectivist Turn in Argument Quality Assessmentcited by 5
  7. 2023MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classificationcited by 4
  8. 2022Detection of Propaganda Techniques in Visuo-Lingual Metaphor in Memescited by 2
  9. 2024Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-fillingcited by 2
  10. 2025Emotionally Charged, Logically Blurred: AI-driven Emotional Framing Impairs Human Fallacy Detectioncited by 2
  11. 2023Modeling Appropriate Language in Argumentationcited by 1
  12. 2025Joint Effects of Argumentation Theory, Audio Modality and Data Enrichment on LLM-Based Fallacy Classificationcited by 1
  13. 2023Teach Me How to Improve My Argumentation Skills: A Survey on Feedback in Argumentationcited by 0
  14. 2026How Ethos and Pathos Appeals Resonate in Reader Interpretations of Social Media Messagescited by 0
  15. 2026A Corpus of Persuasion Techniques in Slavic Languagescited by 0
  16. 2026Retrieving Relations, Detecting Fallacies: A RAG Approach to Political Debate Analysiscited by 0
  17. 2026Fallacy Benchmarks Measure Scheme Recognition, Not Fallacy Detectioncited by 0