mlsanityData to 7 Oct 2026

Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabic

arXiv 2211.10057 ↗First posted 18 Nov 2022cs.CL cs.AI cs.LGcited by 18

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Abstract (arXiv)

Propaganda is the expression of an opinion or an action by an individual or a group deliberately designed to influence the opinions or the actions of other individuals or groups with reference to predetermined ends, which is achieved by means of well-defined rhetorical and psychological devices. Propaganda techniques are commonly used in social media to manipulate or to mislead users. Thus, there has been a lot of recent research on automatic detection of propaganda techniques in text as well as in memes. However, so far the focus has been primarily on English. With the aim to bridge this language gap, we ran a shared task on detecting propaganda techniques in Arabic tweets as part of the WANLP 2022 workshop, which included two subtasks. Subtask~1 asks to identify the set of propaganda techniques used in a tweet, which is a multilabel classification problem, while Subtask~2 asks to detect the propaganda techniques used in a tweet together with the exact span(s) of text in which each propaganda technique appears. The task attracted 63 team registrations, and eventually 14 and 3 teams made submissions for subtask 1 and 2, respectively. Finally, 11 teams submitted system description papers.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 26 of its 65 references that are in the map. First posted on arXiv 18 Nov 2022.

Builds on

26 of 65 references.

References · 26

  1. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  2. 2021A Survey on Automated Fact-Checkingcited by 376
  3. 2019Fine-Grained Analysis of Propaganda in News Articlescited by 130
  4. 2020FANG: Leveraging Social Context for Fake News Detection Using Graph Representationcited by 98
  5. 2020SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articlescited by 79
  6. 2021Detecting Harmful Memes and Their Targetscited by 77
  7. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  8. 2020Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Societycited by 72
  9. 2020A Survey on Computational Propaganda Detectioncited by 69
  10. 2018A Survey on Natural Language Processing for Fake News Detectioncited by 67
  11. 2022Detecting and Understanding Harmful Memes: A Surveycited by 58
  12. 2020SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identificationcited by 53
14 more
  1. 2018A Retrospective Analysis of the Fake News Challenge Stance Detection Taskcited by 49
  2. 2021SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Imagescited by 49
  3. 2021A Survey on Multimodal Disinformation Detectioncited by 47
  4. 2020Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Mediacited by 46
  5. 2021Detecting Propaganda Techniques in Memescited by 43
  6. 2017Argotario: Computational Argumentation Meets Serious Gamescited by 29
  7. 2019Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detectioncited by 24
  8. 2021Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake Newscited by 23
  9. 2021Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claimscited by 18
  10. 2021Interpretable Propaganda Detection in News Articlescited by 16
  11. 2021Findings of the NLP4IF-2021 Shared Tasks on Fighting the COVID-19 Infodemic and Censorship Detectioncited by 14
  12. 2021The Spread of Propaganda by Coordinated Communities on Social Mediacited by 10
  13. 2021A Second Pandemic? Analysis of Fake News About COVID-19 Vaccines in Qatarcited by 5
  14. 2022IITD at the WANLP 2022 Shared Task: Multilingual Multi-Granularity Network for Propaganda Detectioncited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 8; 2024: 6; 2025: 2; 2026: 1.

18 papers.

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  1. 2024Can GPT-4 Identify Propaganda? Annotation and Detection of Propaganda Spans in News Articlescited by 21
  2. 2023ArAIEval Shared Task: Persuasion Techniques and Disinformation Detection in Arabic Textcited by 19
  3. 2024Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicitiescited by 13
  4. 2024Native vs Non-Native Language Prompting: A Comparative Analysiscited by 9
  5. 2024Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-Agent LLMscited by 8
  6. 2023Large Language Models for Propaganda Detectioncited by 7
  7. 2023QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection using Multilingual Modelscited by 5
  8. 2023Legend at ArAIEval Shared Task: Persuasion Technique Detection using a Language-Agnostic Text Representation Modelcited by 4
  9. 2022Data Augmentation using Transformers and Similarity Measures for Improving Arabic Text Classificationcited by 3
  10. 2023Toxic language detection: a systematic review of Arabic datasetscited by 3
  11. 2023USTHB at NADI 2023 shared task: Exploring Preprocessing and Feature Engineering Strategies for Arabic Dialect Identificationcited by 3
  12. 2024A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Modelscited by 3
6 more
  1. 2023Detecting Propaganda Techniques in Code-Switched Social Media Textcited by 1
  2. 2023Mavericks at ArAIEval Shared Task: Towards a Safer Digital Space -- Transformer Ensemble Models Tackling Deception and Persuasioncited by 1
  3. 2024Investigating Persuasion Techniques in Arabic: An Empirical Study Leveraging Large Language Modelscited by 1
  4. 2025Effective Yet Ephemeral Propaganda Defense: There Needs to Be More than One-Shot Inoculation to Enhance Critical Thinkingcited by 1
  5. 2025Fine-grained Narrative Classification in Biased News Articlescited by 0
  6. 2026From Emotion to Expression: Theoretical Foundations and Resources for Fear Speechcited by 0