Annotating Online Misogyny

This is the repository presented in the paper "Annotating Online Misogyny" from ACL 2021.

Annotated Corpus in Danish sampled from Twitter, Facebook, Reddit.

For more information, see the stromberg.ai/publication/aom.

Data access:

Access to the data can be granted under NDA for research purposes. Please fill in this form to submit a request.

By filling the form you submit a request for access to data and annotation.

Repository details

The repository exists of:

• data
• dataset
• out-of-context-posts (sorted out)
• annotation
• codebook
• data_collection_keyword_list
• additional data
• Danish slurs: extending Reddit survey list from Sigurbergsson, Derczynski* on Danish known slurs (free Google search for annotators)
• Translations of posts from IberEval/Evalita (English) to Danish
• counter-examples stereotypes: transforming Danish stereotypical posts to their counter-example (total ~30 posts, tasks turned out to be too challenging)
• additional information from the annotation task
• feedback annotators and motivation

Lastly, feel free to reach out regarding any enquiries around the project.

Referencing the work

Please cite:

Zeinert, P., Inie, N., Derczynski, L., 2021. Annotating Online Misogyny, in: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Presented at the ACL-IJCNLP 2021, Association for Computational Linguistics, Online, pp. 3181–3197.

Bibtex:

@inproceedings{zeinert_annotating_2021,
	address = {Online},
	title = {Annotating {Online} {Misogyny}},
	booktitle = {Proceedings of the 59th {Annual} {Meeting} of the {Association} for {Computational} {Linguistics} and the 11th {International} {Joint} {Conference} on {Natural} {Language} {Processing} ({Volume} 1: {Long} {Papers})},
	publisher = {Association for Computational Linguistics},
	author = {Zeinert, Philine and Inie, Nanna and Derczynski, Leon},
	month = aug,
	year = {2021},
	pages = {3181--3197},
	doi = {http://dx.doi.org/10.18653/v1/2021.acl-long.247}
}