@inproceedings{das-etal-2023-toward,
    title = "Toward Cultural Bias Evaluation Datasets: The Case of {B}engali Gender, Religious, and National Identity",
    author = "Das, Dipto  and
      Guha, Shion  and
      Semaan, Bryan",
    editor = "Dev, Sunipa  and
      Prabhakaran, Vinodkumar  and
      Adelani, David Ifeoluwa  and
      Hovy, Dirk  and
      Benotti, Luciana",
    booktitle = "Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.c3nlp-1.8/",
    doi = "10.18653/v1/2023.c3nlp-1.8",
    pages = "68--83",
    abstract = "Critical studies found NLP systems to bias based on gender and racial identities. However, few studies focused on identities defined by cultural factors like religion and nationality. Compared to English, such research efforts are even further limited in major languages like Bengali due to the unavailability of labeled datasets. This paper describes a process for developing a bias evaluation dataset highlighting cultural influences on identity. We also provide a Bengali dataset as an artifact outcome that can contribute to future critical research."
}