Introducing CAD: the Contextual Abuse Dataset
Publication date
2021-06
Editors
Toutanova, Kristina
Rumshisky, Anna
Zettlemoyer, Luke
Hakkani-Tur, Dilek
Beltagy, Iz
Bethard, Steven
Cotterell, Ryan
Chakraborty, Tanmoy
Zhou, Yichao
Advisors
Supervisors
Document Type
Part of book
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License
cc_by
Abstract
Online abuse can inflict harm on users and communities, making online spaces unsafe and toxic. Progress in automatically detecting and classifying abusive content is often held back by the lack of high quality and detailed datasets.We introduce a new dataset of primarily English Reddit entries which addresses several limitations of prior work. It (1) contains six conceptually distinct primary categories as well as secondary categories, (2) has labels annotated in the context of the conversation thread, (3) contains rationales and (4) uses an expert-driven group-adjudication process for high quality annotations. We report several baseline models to benchmark the work of future researchers. The annotated dataset, annotation guidelines, models and code are freely available.
Keywords
Citation
Vidgen, B, Nguyen, D, Margetts, H, Rossini, P & Tromble, R 2021, Introducing CAD: the Contextual Abuse Dataset. in K Toutanova, A Rumshisky, L Zettlemoyer, D Hakkani-Tur, I Beltagy, S Bethard, R Cotterell, T Chakraborty & Y Zhou (eds), Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, pp. 2289-2303. https://doi.org/10.18653/v1/2021.naacl-main.182