@inproceedings{kukk-etal-2025-biaswe,
title = "{BiaSWE}: {An} Expert Annotated Dataset for Misogyny Detection in {Swedish}",
author = {Kukk, K{\"a}triin and
Petrelli, Danila and
Casademont, Judit and
Orlowski, Eric J. W. and
Dzielinski, Michal and
Jacobson, Maria},
editor = "Johansson, Richard and
Stymne, Sara",
booktitle = "Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)",
month = mar,
year = "2025",
address = "Tallinn, Estonia",
publisher = "University of Tartu Library",
url = "https://aclanthology.org/2025.nodalida-1.33/",
pages = "307--312",
ISBN = "978-9908-53-109-0",
abstract = "In this study, we introduce the process for creating BiaSWE, an expert-annotated dataset tailored for misogyny detection in the Swedish language. To address the cultural and linguistic specificity of misogyny in Swedish, we collaborated with experts from the social sciences and humanities. Our interdisciplinary team developed a rigorous annotation process, incorporating both domain knowledge and language expertise, to capture the nuances of misogyny in a Swedish context. This methodology ensures that the dataset is not only culturally relevant but also aligned with broader efforts in bias detection for low-resource languages. The dataset, along with the annotation guidelines, is publicly available for further research."
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%0 Conference Proceedings
%T BiaSWE: An Expert Annotated Dataset for Misogyny Detection in Swedish
%A Kukk, Kätriin
%A Petrelli, Danila
%A Casademont, Judit
%A Orlowski, Eric J. W.
%A Dzielinski, Michal
%A Jacobson, Maria
%Y Johansson, Richard
%Y Stymne, Sara
%S Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)
%D 2025
%8 March
%I University of Tartu Library
%C Tallinn, Estonia
%@ 978-9908-53-109-0
%F kukk-etal-2025-biaswe
%X In this study, we introduce the process for creating BiaSWE, an expert-annotated dataset tailored for misogyny detection in the Swedish language. To address the cultural and linguistic specificity of misogyny in Swedish, we collaborated with experts from the social sciences and humanities. Our interdisciplinary team developed a rigorous annotation process, incorporating both domain knowledge and language expertise, to capture the nuances of misogyny in a Swedish context. This methodology ensures that the dataset is not only culturally relevant but also aligned with broader efforts in bias detection for low-resource languages. The dataset, along with the annotation guidelines, is publicly available for further research.
%U https://aclanthology.org/2025.nodalida-1.33/
%P 307-312
Markdown (Informal)
[BiaSWE: An Expert Annotated Dataset for Misogyny Detection in Swedish](https://aclanthology.org/2025.nodalida-1.33/) (Kukk et al., NoDaLiDa 2025)
ACL
- Kätriin Kukk, Danila Petrelli, Judit Casademont, Eric J. W. Orlowski, Michal Dzielinski, and Maria Jacobson. 2025. BiaSWE: An Expert Annotated Dataset for Misogyny Detection in Swedish. In Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), pages 307–312, Tallinn, Estonia. University of Tartu Library.