Year: 2025
Type: conference-paper
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.WARNING: the CADE corpus could contain racist, sexist, violent, and generally offensive content.
Authors: Soda Marem Lo, Oscar Araque, Rajesh Sharma, Marco Antonio Stranisci
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412945621