metadata
license: apache-2.0
pretty_name: Cockatoo Moderation V1
size_categories:
- 1M<n<10M
configs:
- config_name: default
data_files:
- split: train
path: source/Cockatoo-Moderation-V1_corpus.parquet
Cockatoo Moderation V1
This dataset is created by merging ucberkeley-dlab/measuring-hate-speech, KoalaAI/Text-Moderation-Multilingual, and google/civil_comments. Thus, this set is subject to different licenses (see below).
Size: 3,399,535 rows
Files:
Cockatoo-Moderation-V1_corpus.parquet: The unlabeled dataset
Cockatoo-Moderation-V1_labeled.parquet: Labeled (coming soon)
Method:
This dataset is primarily synthetically labeled with a small human reviewed subset. More information will be added soon after the labeled set is complete.
Citations:
Google/Civil_Comments (cc0-1.0):
@article{DBLP:journals/corr/abs-1903-04561,
author = {Daniel Borkan and
Lucas Dixon and
Jeffrey Sorensen and
Nithum Thain and
Lucy Vasserman},
title = {Nuanced Metrics for Measuring Unintended Bias with Real Data for Text
Classification},
journal = {CoRR},
volume = {abs/1903.04561},
year = {2019},
url = {http://arxiv.org/abs/1903.04561},
archivePrefix = {arXiv},
eprint = {1903.04561},
timestamp = {Sun, 31 Mar 2019 19:01:24 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1903-04561},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
KoalaAI/Text-Moderation-Multilingual (apache-2.0):
@misc{text-moderation-large,
title={Text-Moderation-Multilingual: A Multilingual Text Moderation Dataset},
author={[KoalaAI]},
year={2025},
note={Aggregated from ifmain's and OpenAI's moderation datasets}
}
ucberkeley-dlab/measuring-hate-speech (cc-by-4.0):
@article{kennedy2020constructing,
title={Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application},
author={Kennedy, Chris J and Bacon, Geoff and Sahn, Alexander and von Vacano, Claudia},
journal={arXiv preprint arXiv:2009.10277},
year={2020}
}