Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-Agent LLMs
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Abstract (arXiv)
In the past decade, social media platforms have been used for information dissemination and consumption. While a major portion of the content is posted to promote citizen journalism and public awareness, some content is posted to mislead users. Among different content types such as text, images, and videos, memes (text overlaid on images) are particularly prevalent and can serve as powerful vehicles for propaganda, hate, and humor. In the current literature, there have been efforts to individually detect such content in memes. However, the study of their intersection is very limited. In this study, we explore the intersection between propaganda and hate in memes using a multi-agent LLM-based approach. We extend the propagandistic meme dataset with coarse and fine-grained hate labels. Our finding suggests that there is an association between propaganda and hate in memes. We provide detailed experimental results that can serve as a baseline for future studies. We will make the experimental resources publicly available to the community (https://github.com/firojalam/propaganda-and-hateful-memes).
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 21 of its 32 references that are in the map. First posted on arXiv 11 Sep 2024.
Builds on
21 of 32 references.
References · 21
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- 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 736
- 2020The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memescited by 490
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- 2019Fine-Grained Analysis of Propaganda in News Articlescited by 133
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9 more
- 2021Detecting Propaganda Techniques in Memescited by 44
- 2021Pre-Training BERT on Arabic Tweets: Practical Considerationscited by 39
- 2024Can GPT-4 Identify Propaganda? Annotation and Detection of Propaganda Spans in News Articlescited by 21
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- 2022Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabiccited by 18
- 2024ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Contentcited by 11
- 2024Deciphering Hate: Identifying Hateful Memes and Their Targetscited by 7
- 2024ArMeme: Propagandistic Content in Arabic Memescited by 5
Built on by
Citing papers per year: 2025: 3; 2026: 5.
8 papers.
- 2025MemeIntel: Explainable Detection of Propagandistic and Hateful Memescited by 10
- 2026MemeLens: Multilingual Multitask VLMs for Memescited by 6
- 2026From Native Memes to Global Moderation: Cross-Cultural Evaluation of Vision-Language Models for Hateful Meme Detectioncited by 2
- 2026ArPoMeme: An Annotated Arabic Multimodal Dataset for Political Ideology and Polarizationcited by 1
- 2025Detecting Hope, Hate, and Emotion in Arabic Textual Speech and Multi-modal Memes Using Large Language Modelscited by 0
- 2025MARSAD: A Multi-Functional Tool for Real-Time Social Media Analysiscited by 0
- 2026Towards High-Level Semantic Intelligencecited by 0
- 2026AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memescited by 0
- 2026AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memes29 Jul 2026
- 2026Towards High-Level Semantic Intelligence27 Jul 2026
- 2026ArPoMeme: An Annotated Arabic Multimodal Dataset for Political Ideology and Polarization20 May 2026
- 2026From Native Memes to Global Moderation: Cross-Cultural Evaluation of Vision-Language Models for Hateful Meme Detection7 Feb 2026
- 2026MemeLens: Multilingual Multitask VLMs for Memes18 Jan 2026
- 2025MARSAD: A Multi-Functional Tool for Real-Time Social Media Analysis1 Dec 2025
- 2025Detecting Hope, Hate, and Emotion in Arabic Textual Speech and Multi-modal Memes Using Large Language Models15 Aug 2025
- 2025MemeIntel: Explainable Detection of Propagandistic and Hateful Memes23 Feb 2025
Similar, not cited
Close in wording, no citation either way
- 2026Is AI Ready for Multimodal Hate Speech Detection? A Comprehensive Dataset and Benchmark Evaluation ↗
- 2026PEST: Parameter Efficient Steering of Blackbox VLMs via Agentic Few-shot Alignment for Hateful Meme Moderation
- 2023A Review of Vision-Language Models and their Performance on the Hateful Memes Challenge
- 2025Demystifying Hateful Content: Leveraging Large Multimodal Models for Hateful Meme Detection with Explainable Decisions
- 2025Detecting and Understanding Hateful Contents in Memes Through Captioning and Visual Question-Answering
- 2025Improving Multimodal Hateful Meme Detection Exploiting LMM-Generated Knowledge
- 2026Beyond Accuracy: A Qualitative Analysis of Vision-Language Models for Hate Speech Detection in Memes
- 2026Adapting Reinforcement Learning with Chain-of-Thought Supervision for Explainable Detection of Hateful and Propagandistic Memes