That is Unacceptable: the Moral Foundations of Canceling

Soda Marem Lo, Oscar Araque, Rajesh Sharma, Marco Antonio Stranisci


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.
Anthology ID:
2025.acl-long.330
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Wanxiang Che, Joyce Nabende, Ekaterina Shutova, Mohammad Taher Pilehvar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6625–6639
Language:
URL:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.330/
DOI:
Bibkey:
Cite (ACL):
Soda Marem Lo, Oscar Araque, Rajesh Sharma, and Marco Antonio Stranisci. 2025. That is Unacceptable: the Moral Foundations of Canceling. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6625–6639, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
That is Unacceptable: the Moral Foundations of Canceling (Lo et al., ACL 2025)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.330.pdf