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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-classification |
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language: |
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- de |
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pretty_name: GAHD |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: "data/gahd.csv" |
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- config_name: gahd_disaggregated |
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data_files: |
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- split: train |
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path: "data/gahd_disaggregated.csv" |
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--- |
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**NOTE** README copied from https://github.com/jagol/gahd |
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This repository contains the dataset from our NAACL 2024 paper "Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset". |
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`gahd.csv` contains the following columns: |
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- `gahd_id`: unique identifier of the entry |
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- `text`: text of the entry |
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- `label`: `0` = "not-hate speech", `1` = "hate speech" |
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- `round`: round in which the entry was created |
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- `split`: "train", "dev", or "test" |
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- `contrastive_gahd_id`: `gahd_id` of its contrastive example |
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`gahd_disaggregated.csv` contains the following additional columns: |
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- `source`: |
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- if annotators entered the entry via the Dynabench interface: `dynabench` |
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- if the entry was translated from the Vidgen et al. 2021 dataset: `translation` |
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- if the entry stems from the Leipzit news corpus: `news` |
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- `model_prediction`: label predicted by the target model, `0` or `1` |
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- `annotator_id`: unique identifier of the annotator that created the entry |
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- `annotator_labels`: a string containing a forward slash-separated list of all labels by annotators |
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- `expert_labels`: `0` or `1` if an expert annotator annotated the entry, otherwise empty |
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When using GAHD, please cite our preprint on Arxiv: |
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``` |
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@misc{goldzycher2024improving, |
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title={Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset}, |
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author={Janis Goldzycher and Paul Röttger and Gerold Schneider}, |
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year={2024}, |
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eprint={2403.19559}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
