Datasets:
Tasks:
Text Classification
Formats:
parquet
Sub-tasks:
multi-label-classification
Languages:
English
Size:
1M - 10M
ArXiv:
License:
language: | |
- en | |
license: cc0-1.0 | |
paperswithcode_id: civil-comments | |
pretty_name: Civil Comments | |
task_categories: | |
- text-classification | |
task_ids: | |
- multi-label-classification | |
dataset_info: | |
features: | |
- name: text | |
dtype: string | |
- name: toxicity | |
dtype: float32 | |
- name: severe_toxicity | |
dtype: float32 | |
- name: obscene | |
dtype: float32 | |
- name: threat | |
dtype: float32 | |
- name: insult | |
dtype: float32 | |
- name: identity_attack | |
dtype: float32 | |
- name: sexual_explicit | |
dtype: float32 | |
splits: | |
- name: train | |
num_bytes: 594805164 | |
num_examples: 1804874 | |
- name: validation | |
num_bytes: 32216880 | |
num_examples: 97320 | |
- name: test | |
num_bytes: 31963524 | |
num_examples: 97320 | |
download_size: 422061071 | |
dataset_size: 658985568 | |
configs: | |
- config_name: default | |
data_files: | |
- split: train | |
path: data/train-* | |
- split: validation | |
path: data/validation-* | |
- split: test | |
path: data/test-* | |
# Dataset Card for "civil_comments" | |
## Table of Contents | |
- [Dataset Description](#dataset-description) | |
- [Dataset Summary](#dataset-summary) | |
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
- [Languages](#languages) | |
- [Dataset Structure](#dataset-structure) | |
- [Data Instances](#data-instances) | |
- [Data Fields](#data-fields) | |
- [Data Splits](#data-splits) | |
- [Dataset Creation](#dataset-creation) | |
- [Curation Rationale](#curation-rationale) | |
- [Source Data](#source-data) | |
- [Annotations](#annotations) | |
- [Personal and Sensitive Information](#personal-and-sensitive-information) | |
- [Considerations for Using the Data](#considerations-for-using-the-data) | |
- [Social Impact of Dataset](#social-impact-of-dataset) | |
- [Discussion of Biases](#discussion-of-biases) | |
- [Other Known Limitations](#other-known-limitations) | |
- [Additional Information](#additional-information) | |
- [Dataset Curators](#dataset-curators) | |
- [Licensing Information](#licensing-information) | |
- [Citation Information](#citation-information) | |
- [Contributions](#contributions) | |
## Dataset Description | |
- **Homepage:** [https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data) | |
- **Repository:** https://github.com/conversationai/unintended-ml-bias-analysis | |
- **Paper:** https://arxiv.org/abs/1903.04561 | |
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
- **Size of downloaded dataset files:** 414.95 MB | |
- **Size of the generated dataset:** 661.23 MB | |
- **Total amount of disk used:** 1.08 GB | |
### Dataset Summary | |
The comments in this dataset come from an archive of the Civil Comments | |
platform, a commenting plugin for independent news sites. These public comments | |
were created from 2015 - 2017 and appeared on approximately 50 English-language | |
news sites across the world. When Civil Comments shut down in 2017, they chose | |
to make the public comments available in a lasting open archive to enable future | |
research. The original data, published on figshare, includes the public comment | |
text, some associated metadata such as article IDs, timestamps and | |
commenter-generated "civility" labels, but does not include user ids. Jigsaw | |
extended this dataset by adding additional labels for toxicity and identity | |
mentions. This data set is an exact replica of the data released for the | |
Jigsaw Unintended Bias in Toxicity Classification Kaggle challenge. This | |
dataset is released under CC0, as is the underlying comment text. | |
### Supported Tasks and Leaderboards | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Languages | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
## Dataset Structure | |
### Data Instances | |
#### default | |
- **Size of downloaded dataset files:** 414.95 MB | |
- **Size of the generated dataset:** 661.23 MB | |
- **Total amount of disk used:** 1.08 GB | |
An example of 'validation' looks as follows. | |
``` | |
{ | |
"identity_attack": 0.0, | |
"insult": 0.0, | |
"obscene": 0.0, | |
"severe_toxicity": 0.0, | |
"sexual_explicit": 0.0, | |
"text": "The public test.", | |
"threat": 0.0, | |
"toxicity": 0.0 | |
} | |
``` | |
### Data Fields | |
The data fields are the same among all splits. | |
#### default | |
- `text`: a `string` feature. | |
- `toxicity`: a `float32` feature. | |
- `severe_toxicity`: a `float32` feature. | |
- `obscene`: a `float32` feature. | |
- `threat`: a `float32` feature. | |
- `insult`: a `float32` feature. | |
- `identity_attack`: a `float32` feature. | |
- `sexual_explicit`: a `float32` feature. | |
### Data Splits | |
| name | train |validation|test | | |
|-------|------:|---------:|----:| | |
|default|1804874| 97320|97320| | |
## Dataset Creation | |
### Curation Rationale | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Source Data | |
#### Initial Data Collection and Normalization | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
#### Who are the source language producers? | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Annotations | |
#### Annotation process | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
#### Who are the annotators? | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Personal and Sensitive Information | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
## Considerations for Using the Data | |
### Social Impact of Dataset | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Discussion of Biases | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Other Known Limitations | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
## Additional Information | |
### Dataset Curators | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Licensing Information | |
This dataset is released under [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/). | |
### Citation Information | |
``` | |
@article{DBLP:journals/corr/abs-1903-04561, | |
author = {Daniel Borkan and | |
Lucas Dixon and | |
Jeffrey Sorensen and | |
Nithum Thain and | |
Lucy Vasserman}, | |
title = {Nuanced Metrics for Measuring Unintended Bias with Real Data for Text | |
Classification}, | |
journal = {CoRR}, | |
volume = {abs/1903.04561}, | |
year = {2019}, | |
url = {http://arxiv.org/abs/1903.04561}, | |
archivePrefix = {arXiv}, | |
eprint = {1903.04561}, | |
timestamp = {Sun, 31 Mar 2019 19:01:24 +0200}, | |
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1903-04561}, | |
bibsource = {dblp computer science bibliography, https://dblp.org} | |
} | |
``` | |
### Contributions | |
Thanks to [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset. |