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HateMM

Introduced by Mithun Das et al. in HateMM: A Multi-Modal Dataset for Hate Video Classification4 Apr 2023 archive 2025-07-28

Hate speech has become one of the most significant issues in modern society, with implications in both the online and offline worlds. However, most of the work has primarily focused on text media, with relatively little work on images and even less on videos. Thus, early-stage automated video moderation techniques are needed to handle the videos that are being uploaded to keep the platform safe and healthy. Therefore, we curated approximately ~43 hours of videos from BitChute and manually annotated them as hate or non-hate, along with the frame spans that could explain the labeling decision.

This upload contains the labeled video dataset crawled from BitChute, as described in the paper 'HateMM: A Multi-modal Dataset for Hate Video Classification'.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Hate Speech Detection HateMM HXP + CLAP + CLIP TEST F1 (macro) 0.848 Towards a Robust Framework for Multimodal Hate... surrey-nlp/Video-vs-Meme-Hate 2 Compare

Papers archive 2025-07-28

2 shown of 2 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 4. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Creative Commons Attribution 4.0 International

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • HateMM

1 variant name, as the archive lists them.

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