mlsanityData to 7 Oct 2026

A Survey on Multimodal Disinformation Detection

arXiv 2103.12541 ↗First posted 13 Mar 2021cs.MM cs.AI cs.CLcited by 47

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Abstract (arXiv)

Recent years have witnessed the proliferation of offensive content online such as fake news, propaganda, misinformation, and disinformation. While initially this was mostly about textual content, over time images and videos gained popularity, as they are much easier to consume, attract more attention, and spread further than text. As a result, researchers started leveraging different modalities and combinations thereof to tackle online multimodal offensive content. In this study, we offer a survey on the state-of-the-art on multimodal disinformation detection covering various combinations of modalities: text, images, speech, video, social media network structure, and temporal information. Moreover, while some studies focused on factuality, others investigated how harmful the content is. While these two components in the definition of disinformation (i) factuality, and (ii) harmfulness, are equally important, they are typically studied in isolation. Thus, we argue for the need to tackle disinformation detection by taking into account multiple modalities as well as both factuality and harmfulness, in the same framework. Finally, we discuss current challenges and future research directions

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). Builds on 67 of its 168 references that are in the map. First posted on arXiv 13 Mar 2021.

Builds on

67 of 168 references.

References · 67

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 12; 2023: 12; 2024: 9; 2025: 5; 2026: 3.

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  1. 2021A Survey on Automated Fact-Checkingcited by 376
  2. 2021Detecting Harmful Memes and Their Targetscited by 77
  3. 2024Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systemscited by 63
  4. 2022Detecting and Understanding Harmful Memes: A Surveycited by 58
  5. 2023Multimodal Automated Fact-Checking: A Surveycited by 51
  6. 2023VERITE: A Robust Benchmark for Multimodal Misinformation Detection Accounting for Unimodal Biascited by 37
  7. 2023Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checkingcited by 34
  8. 2023Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Modelscited by 31
  9. 2023Synthetic Misinformers: Generating and Combating Multimodal Misinformationcited by 23
  10. 2024Can GPT-4 Identify Propaganda? Annotation and Detection of Propaganda Spans in News Articlescited by 21
  11. 2022DISARM: Detecting the Victims Targeted by Harmful Memescited by 20
  12. 2021Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Documentcited by 19
35 more
  1. 2022Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabiccited by 18
  2. 2023RED-DOT: Multimodal Fact-checking via Relevant Evidence Detectioncited by 18
  3. 2023Interpretable Multimodal Misinformation Detection with Logic Reasoningcited by 16
  4. 2022Multi-modal Misinformation Detection: Approaches, Challenges and Opportunitiescited by 14
  5. 2023Combating Online Misinformation Videos: Characterization, Detection, and Future Directionscited by 14
  6. 2022DisinfoMeme: A Multimodal Dataset for Detecting Meme Intentionally Spreading Out Disinformationcited by 13
  7. 2024Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicitiescited by 13
  8. 2021Dataset of Fake News Detection and Fact Verification: A Surveycited by 11
  9. 2023The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Mediacited by 10
  10. 2022CrowdChecked: Detecting Previously Fact-Checked Claims in Social Mediacited by 9
  11. 2023Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AIcited by 9
  12. 2024Native vs Non-Native Language Prompting: A Comparative Analysiscited by 9
  13. 2024Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checkingcited by 8
  14. 2024Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-Agent LLMscited by 8
  15. 2023Findings of Factify 2: Multimodal Fake News Detectioncited by 7
  16. 2022Datavoidant: An AI System for Addressing Political Data Voids on Social Mediacited by 6
  17. 2022GREENER: Graph Neural Networks for News Media Profilingcited by 6
  18. 2025Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Modelscited by 5
  19. 2023Detecting and Reasoning of Deleted Tweets before they are Postedcited by 4
  20. 2021WhatTheWikiFact: Fact-Checking Claims Against Wikipediacited by 3
  21. 2022Multimodal Dual Emotion with Fusion of Visual Sentiment for Rumor Detectioncited by 3
  22. 2025Scaling Reinforcement Learning for Content Moderation with Large Language Modelscited by 3
  23. 2022Detecting the Role of an Entity in Harmful Memes: Techniques and Their Limitationscited by 2
  24. 2026Robust Harmful Meme Detection under Missing Modalities via Shared Representation Learningcited by 2
  25. 2022TeamX@DravidianLangTech-ACL2022: A Comparative Analysis for Troll-Based Meme Classificationcited by 1
  26. 2022Z-Index at CheckThat! Lab 2022: Check-Worthiness Identification on Tweet Textcited by 1
  27. 2024From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Foracited by 1
  28. 2025Latent Reconstruction from Generated Data for Multimodal Misinformation Detectioncited by 1
  29. 2025MultiCheck: Strengthening Web Trust with Unified Multimodal Fact Verificationcited by 1
  30. 2021Logically at Factify 2022: Multimodal Fact Verificationcited by 0
  31. 2024Capturing Pertinent Symbolic Features for Enhanced Content-Based Misinformation Detectioncited by 0
  32. 2024Dynamic Analysis and Adaptive Discriminator for Fake News Detectioncited by 0
  33. 2025Exploring Content and Social Connections of Fake News with Explainable Text and Graph Learningcited by 0
  34. 2026DARC-CLIP: Dynamic Adaptive Refinement with Cross-Attention for Meme Understandingcited by 0
  35. 2026T-IMPACT: A Severity-Aware Benchmark for Contextual Image-Text Manipulationcited by 0