Datasets:
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---
license: mit
dataset_info:
features:
- name: text_id
dtype: string
- name: target
dtype: string
- name: text
dtype: string
- name: annotator_id
dtype: string
- name: stakeholder
dtype: string
- name: stance
dtype: float64
- name: acceptability
dtype: float64
- name: sample
dtype: string
- name: comment
dtype: string
- name: care
dtype: float64
- name: fairness
dtype: float64
- name: loyalty
dtype: float64
- name: authority
dtype: float64
- name: purity
dtype: float64
- name: cluster
dtype: int64
- name: Gender identity
dtype: string
- name: annotation_id
dtype: string
splits:
- name: train
num_bytes: 3921377
num_examples: 11935
download_size: 1073193
dataset_size: 3921377
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-classification
language:
- en
tags:
- acceptability
- stance
- content-moderation
- canceling
- cancel-culture
- hate-speech
- moral-foundations-theory
pretty_name: cade
size_categories:
- 10K<n<100K
---
# The Canceling Attitudes Detection (CADE) Dataset
CADE is a dataset created in the context of the research [**That is Unacceptable: the Moral Foundations of Canceling**](https://arxiv.org/pdf/2503.05720). Here you can find the 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 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.
## If you use the dataset please cite this work
```
@misc{lo2025unacceptablemoralfoundationscanceling,
title={That is Unacceptable: the Moral Foundations of Canceling},
author={Soda Marem Lo and Oscar Araque and Rajesh Sharma and Marco Antonio Stranisci},
year={2025},
eprint={2503.05720},
archivePrefix={arXiv},
primaryClass={cs.CY},
url={https://arxiv.org/abs/2503.05720},
}
```
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