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AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages vs MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition

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.

AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African LanguagesMasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
Category
Research
Research
Type
NLP benchmark
NLP benchmark
Country
🌍 Pan-African
🌍 Pan-African
Docs status
Docs live
Docs live
Licensing
Pricing
Free / open
Free / open
Verified
Unverified
Unverified
Last verified
10 Oct 2026
10 Oct 2026
Tags
african-languages, hate-speech, nlp-benchmark, content-moderation
named-entity-recognition, african-languages, nlp-benchmark, transfer-learning
Links
Website
Website
Summary
AfriHate is a multilingual benchmark of hate speech and abusive language datasets covering 15 African languages, annotated by native speakers. The paper contributes classification baselines and hate speech and offensive language lexicons, and analyses why keyword-based moderation fails for low-resource African languages. It was released on arXiv in January 2025.
MasakhaNER 2.0 introduces the largest human-annotated named entity recognition dataset for 20 African languages and studies Africa-centric cross-lingual transfer learning. The paper reports that choosing the best transfer language improves zero-shot F1 by an average of 14 points across the 20 languages compared with transferring from English.

AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages vs MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition at a glance

AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages and MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition are both listed under NLP benchmark in Wycord's Research 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: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages (36 checks) and 100% for MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition (36 checks).

Average response time on live probes was 6 ms for AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages and 24 ms for MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition.

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

How they differ

  • Average latency: AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages, 6 ms; MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition, 24 ms.

Topics

Both are tagged: african-languages, nlp-benchmark.

Only AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages: hate-speech, content-moderation.

Only MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition: named-entity-recognition, transfer-learning.

Common questions

Which has better uptime, AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages or MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition?
They are level at 100% over the last 30 days.
Do AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages or MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition need approval before use?
Both are marked "No approval needed".
Is the documentation for AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages and MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition working?
Both show "Docs live" at the last check.
Where are AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages and MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition based?
Both are based in Pan-African.

More comparisons

Full details: AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African LanguagesFull details: MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition