M3 CHEM Twitter Multimodal Hate Speech Dataset
A Twitter/X dataset of 526 multimodal posts (132 hate, 394 non-hate), collected by Mira AI Lab (2024). Each record contains image filename, image OCR text, post text, hate/non-hate binary label, hate category (gender/race/religion/politics/violence/health/etc), and human-annotated reason for classification. Multimodal Twitter subset hate speech dataset combining image OCR text and post text with fine-grained category labels across 8 hate dimensions — 25% of posts are hate speech with human-annotated reasoning. Suitable for multimodal hate speech detection, cross-platform analysis, hate category classification, image-text hate speech, content moderation research. The package includes the 526 meme images (img/) that the records name.
Cite this dataset at
m3-chem-twitter.echo.directory
Analytics
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Computed over the full corpus.
Record
- Catalog key
m3-chem-twitter- Authors
- Xing, Rui; Chai, Qi; Ma, Jie; Tao, Jing; Wang, Pinghui; Zhang, Shuming; Wang, Xinping; Wang, Hao
- Year
- 2026
- Source paper
- Is AI Ready for Multimodal Hate Speech Detection? A Comprehensive Dataset and Benchmark Evaluation
- DOI / arXiv
- 10.48550/arXiv.2603.21686
- License
- Academic research use — see repository (LicenseRef-Research-Only)
- Records
- 526
- Nodes are
- unknown
- Edges are
- unknown
- Text corpus
- social media post text and image OCR text
- Languages
- en, zh
- Collected
- 2024 (2020s)
- Tasks
- Hate speech detection (binary;
is_hate) inferred - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://github.com/mira-ai-lab/M3 link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-21, 69.9 MB across 527 files. Checksums in MANIFEST.json.
Citations
Is AI Ready for Multimodal Hate Speech Detection? A Comprehensive Dataset and Benchmark Evaluation
Rui Xing, Qi Chai, Jie Ma, Jing Tao, Ping-Hui Wang
Journal Article · arXiv.org · 2026
Cited by
- unibo_ccmmd@CC-MMD: Cross-Cultural Misogynistic Meme Detection with Qwen3-VL-8B-Instruct and 4-bit QLoRA
Ming-Gui Duan, P. Gajo et al. · Proceedings of the 28th International Conference On Multimodal Interaction · 2026 · cited 1× - Algorithmic Panic, Cultural Misalignment, and Multimodal Over Filtration in AI Processing of Obfuscated Arabic Political Image-Texts about the USA–Israel–Iran Conflict
Reima Al-Jarf · Frontiers in Computer Science and Artificial Intelligence · 2026 · cited 0×
Citation data from Semantic Scholar, retrieved 2026-10-22.
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@misc{https://doi.org/10.48550/arxiv.2603.21686,
doi = {10.48550/ARXIV.2603.21686},
url = {https://arxiv.org/abs/2603.21686},
author = {Xing, Rui and Chai, Qi and Ma, Jie and Tao, Jing and Wang, Pinghui and Zhang, Shuming and Wang, Xinping and Wang, Hao},
keywords = {Multiagent Systems (cs.MA), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Is AI Ready for Multimodal Hate Speech Detection? A Comprehensive Dataset and Benchmark Evaluation},
publisher = {arXiv},
year = {2026},
copyright = {arXiv.org perpetual, non-exclusive license}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Xing, R., Chai, Q., Ma, J., Tao, J., Wang, P., Zhang, S., Wang, X., & Wang, H. (2026). M3 CHEM Twitter Multimodal Hate Speech Dataset [Data set]. https://doi.org/10.48550/arXiv.2603.21686
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Xing, Rui, et al. M3 CHEM Twitter Multimodal Hate Speech Dataset. 2026, doi.org/10.48550/arXiv.2603.21686.