README.md

metadata

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.

Languages

All text is written in English.

Dataset Structure

Data Fields

We release TwitCivility as a data frame with the following fields:
text: This field contains the text (after preprocessing and anonymization) of the tweet.
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.
intolerance: Similarly, this binary value denotes the presence of intolerance in the text, with 1 indicating intolerance and 0 signifying non-intolerance.

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}
}