Datasets:
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---
license: mit
dataset_info:
features:
- name: text
dtype: string
- name: impoliteness
dtype: int64
- name: intolerance
dtype: int64
splits:
- name: train
num_bytes: 2169574.4014020115
num_examples: 10498
- name: test
num_bytes: 542703.5985979884
num_examples: 2626
download_size: 1726706
dataset_size: 2712278
task_categories:
- text-classification
language:
- en
---
## Overview
The TwitCivility dataset is specifically developed to classify political incivility, focusing on multidimensional aspects of impoliteness and intolerance.
Detailed methodologies are outlined in our [paper](https://arxiv.org/abs/2305.14964).
## Languages
All text is written in English.
## Dataset Structure
### Data Fields
We release TwitCivility as a data frame with the following fields: <br />
**text**: This field contains the text (after preprocessing and anonymization) of the tweet. <br />
**impoliteness**: A binary indicator (1 or 0) representing the presence of impoliteness in the text. A value of 1 signifies impoliteness, while 0 indicates non-impoliteness. <br />
**intolerance**: Similarly, this binary value denotes the presence of intolerance in the text, with 1 indicating intolerance and 0 signifying non-intolerance. <br />
## Citation Information
```
@misc{incivility2023,
title={Detecting Multidimensional Political Incivility on Social Media},
author={Sagi Pendzel and Nir Lotan and Alon Zoizner and Einat Minkov},
year={2023},
eprint={2305.14964},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
``` |