Abstract
Online Gender-Based Violence (GBV), such as misogynistic abuse, is an increasingly prevalent problem that technological approaches have struggled to address. Through the lens of the GBV framework, which is rooted in social science and policy, we systematically review 63 available resources for automated identification of such language. We find the datasets are limited in a number of important ways, such as their lack of theoretical grounding and stakeholder input, static nature, and focus on certain media platforms. Based on this review, we recommend development of future resources rooted in sociological expertise and centering stakeholder voices, namely GBV experts and people with lived experience of GBV.
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CITATION STYLE
Abercrombie, G., Jiang, A., Gerrard-Abbott, P., Konstas, I., & Rieser, V. (2023). Resources for Automated Identification of Online Gender-Based Violence: A Systematic Review. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 170–186). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.woah-1.17
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