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@@ -22,23 +22,23 @@ pretty_name: dynamically generated hate speech dataset
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  This is a copy of the Dynamically-Generated-Hate-Speech-Dataset, presented in [this paper](https://arxiv.org/abs/2012.15761) by
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  - **Bertie Vidgen**, **Tristan Thrush**, **Zeerak Waseem** and **Douwe Kiela**
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- This repository only contains v0.2.3, I have not many any additional changes to this paper.
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  ## Original README from [GitHub](https://github.com/bvidgen/Dynamically-Generated-Hate-Speech-Dataset/blob/main/README.md)
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- # Dynamically-Generated-Hate-Speech-Dataset
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  ReadMe for v0.2 of the Dynamically Generated Hate Speech Dataset from Vidgen et al. (2021). If you use the dataset, please cite our paper in the Proceedings of ACL 2021, and available on [Arxiv](https://arxiv.org/abs/2012.15761).
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  Contact Dr. Bertie Vidgen if you have feedback or queries: [email protected].
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  The full author list is: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research). This paper is an output of the Dynabench project: https://dynabench.org/tasks/5#overall
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- ## Dataset descriptions
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  v0.2.2.csv is the full dataset used in our ACL paper.
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  v0.2.3.csv removes duplicate entries, all of which occurred in round 1. Duplicates come from two sources: (1) annotators entering the same content multiple times and (2) different annotators entering the same content. The duplicates are interesting for understanding the annotation process, and the challenges of dynamically generating datasets. However, they are likely to be less useful for training classifiers and so are removed in v0.2.3. We did not lower case the text before removing duplicates as capitalisations contain potentially useful signals.
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- ## Overview
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  The Dynamically Generated Hate Speech Dataset is provided in one table.
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  'acl.id' is the unique ID of the entry.
@@ -118,7 +118,7 @@ This repository only contains v0.2.3, I have not many any additional changes to
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  nazi -> Nazis ('Support' type of hate)
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  hitler -> Hitler ('Support' type of hate)
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- ## Code
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  Code was implemented using hugging face transformers library.
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  ## Additional Information
 
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  This is a copy of the Dynamically-Generated-Hate-Speech-Dataset, presented in [this paper](https://arxiv.org/abs/2012.15761) by
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  - **Bertie Vidgen**, **Tristan Thrush**, **Zeerak Waseem** and **Douwe Kiela**
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+ **This repository only contains v0.2.3, I have not made any additional changes and don't own this work!**
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  ## Original README from [GitHub](https://github.com/bvidgen/Dynamically-Generated-Hate-Speech-Dataset/blob/main/README.md)
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+ ## Dynamically-Generated-Hate-Speech-Dataset
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  ReadMe for v0.2 of the Dynamically Generated Hate Speech Dataset from Vidgen et al. (2021). If you use the dataset, please cite our paper in the Proceedings of ACL 2021, and available on [Arxiv](https://arxiv.org/abs/2012.15761).
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  Contact Dr. Bertie Vidgen if you have feedback or queries: [email protected].
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  The full author list is: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research). This paper is an output of the Dynabench project: https://dynabench.org/tasks/5#overall
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+ ### Dataset descriptions
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  v0.2.2.csv is the full dataset used in our ACL paper.
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  v0.2.3.csv removes duplicate entries, all of which occurred in round 1. Duplicates come from two sources: (1) annotators entering the same content multiple times and (2) different annotators entering the same content. The duplicates are interesting for understanding the annotation process, and the challenges of dynamically generating datasets. However, they are likely to be less useful for training classifiers and so are removed in v0.2.3. We did not lower case the text before removing duplicates as capitalisations contain potentially useful signals.
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+ ### Overview
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  The Dynamically Generated Hate Speech Dataset is provided in one table.
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  'acl.id' is the unique ID of the entry.
 
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  nazi -> Nazis ('Support' type of hate)
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  hitler -> Hitler ('Support' type of hate)
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+ ### Code
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  Code was implemented using hugging face transformers library.
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  ## Additional Information