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