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Datasets

AfriHate Hate Speech Datasets vs MasakhaNER 2.0

A verified, side-by-side comparison. Both records are status-checked by Wycord, so you are comparing what each actually offers today, not a stale listing.

Category
Datasets
Datasets
Type
Language / NLP
Language / NLP
Country
🌍 Pan-African
🌍 Pan-African
Docs status
Docs live
Docs live
Licensing
Pricing
Free / open
Free / CC-BY-NC 4.0
Verified
Unverified
Verified
Last verified
10 Oct 2026
10 Oct 2026
Tags
nlp, african-languages, hate-speech, abusive-language, twitter
nlp, ner, named-entity-recognition, african-languages, token-classification
Summary
Multilingual collection of hate speech and abusive language datasets covering 15 African languages, built from tweets annotated by native speakers. Each instance carries labels from 3 to 4 annotators with anonymous annotator IDs, downloadable on HuggingFace. Published at NAACL 2025.
Largest high-quality named-entity-recognition corpus for 20 African languages (incl. Nigerian Pidgin, Hausa, Igbo, Yoruba) with PER/ORG/LOC/DATE tags over news-domain text, totaling ~152,786 rows. Built by the Masakhane community.

AfriHate Hate Speech Datasets vs MasakhaNER 2.0 at a glance

AfriHate Hate Speech Datasets and MasakhaNER 2.0 are both listed under Language / NLP in Wycord's Datasets index.

Both are based in Pan-African.

Both currently show the status "Docs live".

On access, both are marked "No approval needed".

Over the last 30 days Wycord's probes measured 100% uptime for AfriHate Hate Speech Datasets (36 checks) and 100% for MasakhaNER 2.0 (36 checks).

Average response time on live probes was 139 ms for AfriHate Hate Speech Datasets and 242 ms for MasakhaNER 2.0.

Uptime and latency come from Wycord's own probes of each resource's website, documentation and repository, run every six hours.

How they differ

  • Pricing: AfriHate Hate Speech Datasets, Free / open; MasakhaNER 2.0, Free / CC-BY-NC 4.0.
  • Verification: AfriHate Hate Speech Datasets, Unverified; MasakhaNER 2.0, Verified.
  • Average latency: AfriHate Hate Speech Datasets, 139 ms; MasakhaNER 2.0, 242 ms.

Topics

Both are tagged: nlp, african-languages.

Only AfriHate Hate Speech Datasets: hate-speech, abusive-language, twitter.

Only MasakhaNER 2.0: ner, named-entity-recognition, token-classification.

Common questions

Which has better uptime, AfriHate Hate Speech Datasets or MasakhaNER 2.0?
They are level at 100% over the last 30 days.
Do AfriHate Hate Speech Datasets or MasakhaNER 2.0 need approval before use?
Both are marked "No approval needed".
Is the documentation for AfriHate Hate Speech Datasets and MasakhaNER 2.0 working?
Both show "Docs live" at the last check.
Where are AfriHate Hate Speech Datasets and MasakhaNER 2.0 based?
Both are based in Pan-African.

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