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Replace YAML keys from int to str (#2)
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---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
pretty_name: Jigsaw Unintended Bias in Toxicity Classification
tags:
- toxicity-prediction
dataset_info:
features:
- name: target
dtype: float32
- name: comment_text
dtype: string
- name: severe_toxicity
dtype: float32
- name: obscene
dtype: float32
- name: identity_attack
dtype: float32
- name: insult
dtype: float32
- name: threat
dtype: float32
- name: asian
dtype: float32
- name: atheist
dtype: float32
- name: bisexual
dtype: float32
- name: black
dtype: float32
- name: buddhist
dtype: float32
- name: christian
dtype: float32
- name: female
dtype: float32
- name: heterosexual
dtype: float32
- name: hindu
dtype: float32
- name: homosexual_gay_or_lesbian
dtype: float32
- name: intellectual_or_learning_disability
dtype: float32
- name: jewish
dtype: float32
- name: latino
dtype: float32
- name: male
dtype: float32
- name: muslim
dtype: float32
- name: other_disability
dtype: float32
- name: other_gender
dtype: float32
- name: other_race_or_ethnicity
dtype: float32
- name: other_religion
dtype: float32
- name: other_sexual_orientation
dtype: float32
- name: physical_disability
dtype: float32
- name: psychiatric_or_mental_illness
dtype: float32
- name: transgender
dtype: float32
- name: white
dtype: float32
- name: created_date
dtype: string
- name: publication_id
dtype: int32
- name: parent_id
dtype: float32
- name: article_id
dtype: int32
- name: rating
dtype:
class_label:
names:
'0': rejected
'1': approved
- name: funny
dtype: int32
- name: wow
dtype: int32
- name: sad
dtype: int32
- name: likes
dtype: int32
- name: disagree
dtype: int32
- name: sexual_explicit
dtype: float32
- name: identity_annotator_count
dtype: int32
- name: toxicity_annotator_count
dtype: int32
splits:
- name: train
num_bytes: 914264058
num_examples: 1804874
- name: test_private_leaderboard
num_bytes: 49188921
num_examples: 97320
- name: test_public_leaderboard
num_bytes: 49442360
num_examples: 97320
download_size: 0
dataset_size: 1012895339
---
# Dataset Card for Jigsaw Unintended Bias in Toxicity Classification
## Table of Contents
- [Table of Contents](#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
- **Repository:**
- **Paper:**
- **Leaderboard:** https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/leaderboard
- **Point of Contact:**
### Dataset Summary
The Jigsaw Unintended Bias in Toxicity Classification dataset comes from the eponymous Kaggle competition.
Please see the original [data](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data)
description for more information.
### Supported Tasks and Leaderboards
The main target for this dataset is toxicity prediction. Several toxicity subtypes are also available, so the dataset
can be used for multi-attribute prediction.
See the original [leaderboard](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/leaderboard)
for reference.
### Languages
English
## Dataset Structure
### Data Instances
A data point consists of an id, a comment, the main target, the other toxicity subtypes as well as identity attributes.
For instance, here's the first train example.
```
{
"article_id": 2006,
"asian": NaN,
"atheist": NaN,
"bisexual": NaN,
"black": NaN,
"buddhist": NaN,
"christian": NaN,
"comment_text": "This is so cool. It's like, 'would you want your mother to read this??' Really great idea, well done!",
"created_date": "2015-09-29 10:50:41.987077+00",
"disagree": 0,
"female": NaN,
"funny": 0,
"heterosexual": NaN,
"hindu": NaN,
"homosexual_gay_or_lesbian": NaN,
"identity_annotator_count": 0,
"identity_attack": 0.0,
"insult": 0.0,
"intellectual_or_learning_disability": NaN,
"jewish": NaN,
"latino": NaN,
"likes": 0,
"male": NaN,
"muslim": NaN,
"obscene": 0.0,
"other_disability": NaN,
"other_gender": NaN,
"other_race_or_ethnicity": NaN,
"other_religion": NaN,
"other_sexual_orientation": NaN,
"parent_id": NaN,
"physical_disability": NaN,
"psychiatric_or_mental_illness": NaN,
"publication_id": 2,
"rating": 0,
"sad": 0,
"severe_toxicity": 0.0,
"sexual_explicit": 0.0,
"target": 0.0,
"threat": 0.0,
"toxicity_annotator_count": 4,
"transgender": NaN,
"white": NaN,
"wow": 0
}
```
### Data Fields
- `id`: id of the comment
- `target`: value between 0(non-toxic) and 1(toxic) classifying the comment
- `comment_text`: the text of the comment
- `severe_toxicity`: value between 0(non-severe_toxic) and 1(severe_toxic) classifying the comment
- `obscene`: value between 0(non-obscene) and 1(obscene) classifying the comment
- `identity_attack`: value between 0(non-identity_hate) or 1(identity_hate) classifying the comment
- `insult`: value between 0(non-insult) or 1(insult) classifying the comment
- `threat`: value between 0(non-threat) and 1(threat) classifying the comment
- For a subset of rows, columns containing whether the comment mentions the entities (they may contain NaNs):
- `male`
- `female`
- `transgender`
- `other_gender`
- `heterosexual`
- `homosexual_gay_or_lesbian`
- `bisexual`
- `other_sexual_orientation`
- `christian`
- `jewish`
- `muslim`
- `hindu`
- `buddhist`
- `atheist`
- `other_religion`
- `black`
- `white`
- `asian`
- `latino`
- `other_race_or_ethnicity`
- `physical_disability`
- `intellectual_or_learning_disability`
- `psychiatric_or_mental_illness`
- `other_disability`
- Other metadata related to the source of the comment, such as creation date, publication id, number of likes,
number of annotators, etc:
- `created_date`
- `publication_id`
- `parent_id`
- `article_id`
- `rating`
- `funny`
- `wow`
- `sad`
- `likes`
- `disagree`
- `sexual_explicit`
- `identity_annotator_count`
- `toxicity_annotator_count`
### Data Splits
There are four splits:
- train: The train dataset as released during the competition. Contains labels and identity information for a
subset of rows.
- test: The train dataset as released during the competition. Does not contain labels nor identity information.
- test_private_expanded: The private leaderboard test set, including toxicity labels and subgroups. The competition target was a binarized version of the toxicity column, which can be easily reconstructed using a >=0.5 threshold.
- test_public_expanded: The public leaderboard test set, including toxicity labels and subgroups. The competition target was a binarized version of the toxicity column, which can be easily reconstructed using a >=0.5 threshold.
## Dataset Creation
### Curation Rationale
The dataset was created to help in efforts to identify and curb instances of toxicity online.
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
This dataset is released under CC0, as is the underlying comment text.
### Citation Information
No citation is available for this dataset, though you may link to the [kaggle](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification) competition
### Contributions
Thanks to [@iwontbecreative](https://github.com/iwontbecreative) for adding this dataset.