OffensEval 2020 — All Languages Combined
A Twitter (OffensEval 2020 — 5 languages) dataset of 61,922 tweets across 5 languages with offensive/non-offensive labels, collected by Zampieri et al. for SemEval-2020 Task 12. Each record contains tweet text, binary offensive label (OFF/NOT), language, split. Combined OffensEval 2020 benchmark across Arabic, Danish, English, Greek, and Turkish — 61,922 tweets from the most-participated SemEval task ever (528 teams). Suitable for multilingual offensive language detection, cross-lingual transfer, content moderation, NLP benchmarking.
Cite this dataset at
offenseval2020-all.echo.directory
Analytics
Topic 0
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 7
Topic 8
Topic 9
Topic 10
Topic 11
Show all 22 topics
Topic 12
Topic 13
Topic 14
Topic 15
Topic 16
Topic 17
Topic 18
Topic 19
Topic 20
Topic 21
Computed over the full corpus.
Record
- Catalog key
offenseval2020-all- Authors
- Zampieri, Marcos; Nakov, Preslav; Rosenthal, Sara; Atanasova, Pepa; Karadzhov, Georgi; Mubarak, Hamdy; Derczynski, Leon; Pitenis, Zeses; Coltekin, Cagri
- Year
- 2020
- Source paper
- SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)
- DOI / arXiv
- 10.18653/v1/2020.semeval-1.188
- License
- CC BY 4.0 (CC-BY-4.0)
- Records
- 61,922
- Languages
- ar, da, el, en, tr
- Collected
- 2020 (2020s)
- Tasks
- Toxicity detection (binary;
is_offensive) inferred - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://huggingface.co/datasets/strombergnlp/offenseval_2020 link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-02, 8.8 MB across 14 files. Checksums in MANIFEST.json.
Citations
SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)
Marcos Zampieri, Preslav Nakov, Sara Rosenthal, Pepa Atanasova, Georgi Karadzhov
Journal Article · International Workshop on Semantic Evaluation · 2020
Cited by
- Resources and benchmark corpora for hate speech detection: a systematic review
Fabio Poletto, Valerio Basile et al. · Language Resources and Evaluation · 2020 · cited 517× - GPT is an effective tool for multilingual psychological text analysis
Steve Rathje, Dan-Mircea Mirea et al. · Proceedings of the National Academy of Sciences of the United States of America · 2024 · cited 420× - Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection
Bertie Vidgen, Tristan Thrush et al. · Annual Meeting of the Association for Computational Linguistics · 2021 · cited 394× - Directions in abusive language training data, a systematic review: Garbage in, garbage out
Bertie Vidgen, Leon Derczynski · PLoS ONE · 2020 · cited 392× - KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media
Ali Safaya, Moutasem Abdullatif et al. · International Workshop on Semantic Evaluation · 2020 · cited 391×
Show all 10
- Recipes for Safety in Open-domain Chatbots
Jing Xu, Da Ju et al. · arXiv.org · 2020 · cited 260× - SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification
E. Fersini, F. Gasparini et al. · International Workshop on Semantic Evaluation · 2022 · cited 246× - Towards generalisable hate speech detection: a review on obstacles and solutions
Wenjie Yin, A. Zubiaga · PeerJ Computer Science · 2021 · cited 221× - Multilingual Offensive Language Identification with Cross-lingual Embeddings
Tharindu Ranasinghe, Marcos Zampieri · Conference on Empirical Methods in Natural Language Processing · 2020 · cited 188× - SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identification
Sara Rosenthal, Pepa Atanasova et al. · Findings · 2020 · cited 188×
Citation data from Semantic Scholar, retrieved 2026-10-19.
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}
}
@inproceedings{zampieri2020semeval,
title = {SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)},
author = {Zampieri, Marcos and Nakov, Preslav and Rosenthal, Sara and Atanasova, Pepa and Karadzhov, Georgi and Mubarak, Hamdy and Derczynski, Leon and Pitenis, Zeses and Coltekin, Cagri},
booktitle = {SemEval},
year = {2020}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Zampieri, M., Nakov, P., Rosenthal, S., Atanasova, P., Karadzhov, G., Mubarak, H., Derczynski, L., Pitenis, Z., & Coltekin, C. (2020). OffensEval 2020 — All Languages Combined [Data set]. https://doi.org/10.18653/v1/2020.semeval-1.188
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Zampieri, Marcos, et al. OffensEval 2020 — All Languages Combined. 2020, doi.org/10.18653/v1/2020.semeval-1.188.