Canceling is a morally-driven phenomenon that hinders the development of safe social media platforms and contributes to ideological polarization. To address this issue we present the Canceling Attitudes Detection (CADE) dataset, an annotated corpus of canceling incidents aimed at exploring the factors of disagreements in evaluating people’s canceling attitudes on social media. Specifically, we study the impact of annotators’ morality in their perception of canceling, showing that morality is an independent axis for the explanation of disagreement on this phenomenon. Annotator’s judgments heavily depend on the type of controversial events and involved celebrities. This shows the need to develop more event-centric datasets to better understand how harms are perpetrated in social media and to develop more aware technologies for their detection.

That is Unacceptable: the Moral Foundations of Canceling

Soda Marem Lo
First
Membro del Collaboration Group
;
Marco Antonio Stranisci
Last
Membro del Collaboration Group
2025-01-01

Abstract

Canceling is a morally-driven phenomenon that hinders the development of safe social media platforms and contributes to ideological polarization. To address this issue we present the Canceling Attitudes Detection (CADE) dataset, an annotated corpus of canceling incidents aimed at exploring the factors of disagreements in evaluating people’s canceling attitudes on social media. Specifically, we study the impact of annotators’ morality in their perception of canceling, showing that morality is an independent axis for the explanation of disagreement on this phenomenon. Annotator’s judgments heavily depend on the type of controversial events and involved celebrities. This shows the need to develop more event-centric datasets to better understand how harms are perpetrated in social media and to develop more aware technologies for their detection.
2025
63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Vienna
27/07/2025-01/08/2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Association for Computational Linguistics (ACL)
1
6625
6639
human-label variation, moral pluralism, cancel culture, hate spech detection
Soda Marem Lo, Oscar Araque, Rajesh Sharma, Marco Antonio Stranisci
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2102660
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