Datasets:

google
/

jigsaw_toxicity_pred

Name: jigsaw_toxicity_pred
Creator: Google
License: https://choosealicense.com/licenses/cc0-1.0/

Tasks:

Text Classification

Sub-tasks:

multi-label-classification

Languages:

English

Size:

100K<n<1M

License:

Dataset card Files Files and versions Community

Dataset Viewer

Full Screen Viewer

Full Screen

The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

Dataset Card for [Dataset Name]

Dataset Summary

Discussing things you care about can be difficult. The threat of abuse and harassment online means that many people stop expressing themselves and give up on seeking different opinions. Platforms struggle to effectively facilitate conversations, leading many communities to limit or completely shut down user comments. This dataset consists of a large number of Wikipedia comments which have been labeled by human raters for toxic behavior.

Supported Tasks and Leaderboards

The dataset support multi-label classification

Languages

The comments are in English

Dataset Structure

Data Instances

A data point consists of a comment followed by multiple labels that can be associated with it. {'id': '02141412314', 'comment_text': 'Sample comment text', 'toxic': 0, 'severe_toxic': 0, 'obscene': 0, 'threat': 0, 'insult': 0, 'identity_hate': 1, }

Data Fields

id: id of the comment
comment_text: the text of the comment
toxic: value of 0(non-toxic) or 1(toxic) classifying the comment
severe_toxic: value of 0(non-severe_toxic) or 1(severe_toxic) classifying the comment
obscene: value of 0(non-obscene) or 1(obscene) classifying the comment
threat: value of 0(non-threat) or 1(threat) classifying the comment
insult: value of 0(non-insult) or 1(insult) classifying the comment
identity_hate: value of 0(non-identity_hate) or 1(identity_hate) classifying the comment

Data Splits

The data is split into a training and testing set.

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

The dataset is a collection of Wikipedia comments.

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

If words that are associated with swearing, insults or profanity are present in a comment, it is likely that it will be classified as toxic, regardless of the tone or the intent of the author e.g. humorous/self-deprecating. This could present some biases towards already vulnerable minority groups.