README.md

metadata

license: cc-by-4.0
task_categories:
  - text-classification
language:
  - de
pretty_name: GAHD
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/gahd.csv
  - config_name: gahd_disaggregated
    data_files:
      - split: train
        path: data/gahd_disaggregated.csv

NOTE README copied from https://github.com/jagol/gahd

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".

gahd.csv contains the following columns:

• gahd_id: unique identifier of the entry
• text: text of the entry
• label: 0 = "not-hate speech", 1 = "hate speech"
• round: round in which the entry was created
• split: "train", "dev", or "test"
• contrastive_gahd_id: gahd_id of its contrastive example

gahd_disaggregated.csv contains the following additional columns:

• source:
  • if annotators entered the entry via the Dynabench interface: dynabench
  • if the entry was translated from the Vidgen et al. 2021 dataset: translation
  • if the entry stems from the Leipzit news corpus: news
• model_prediction: label predicted by the target model, 0 or 1
• annotator_id: unique identifier of the annotator that created the entry
• annotator_labels: a string containing a forward slash-separated list of all labels by annotators
• expert_labels: 0 or 1 if an expert annotator annotated the entry, otherwise empty

When using GAHD, please cite our preprint on Arxiv:

@misc{goldzycher2024improving,
      title={Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset}, 
      author={Janis Goldzycher and Paul Röttger and Gerold Schneider},
      year={2024},
      eprint={2403.19559},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}