Identify and classify toxic online comments

November 11, 2021 - jigsaw-toxic-comment-classification-challenge+1 · arrow_drop_up408 · table_chart · jigsaw-unintended-bias-in-toxicity-classificationmore_vert · Julián Peller (dataista0) Usability 7.1 · Updated 5 years ago · 8 Files (CSV) · 759 MB · 1,971 downloads ·

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Kaggle Competition: Toxic Comments Classification (Link: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge) - iampukar/toxic-comments-classification

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Disclaimer: the dataset for this competition contains text that may be considered profane, vulgar, or offensive. From https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge

November 11, 2021 - Data from Toxic Comment Classification Challenge

In the meantime, platforms struggle to effectively facilitate conversations, leading many communities to limit or completely shut down user comments. Therefore, Kaggle started this competition with the Conversation AI team, a research initiative founded by Jigsaw and Google. The competition could be found here: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge

Jigsaw/Conversation AI · Featured Code Competition ·

# create data directory mkdir jigsaw_data cd jigsaw_data # download data kaggle competitions download -c jigsaw-toxic-comment-classification-challenge kaggle competitions download -c jigsaw-unintended-bias-in-toxicity-classification kaggle competitions download -c jigsaw-multilingual-toxic-comment-classification

Use TPUs to identify toxicity comments across multiple languages

This was my first Kaggle challenge that I took seriously and I managed to get into the top 3% (119th place out of 4550 teams) - nothing to brag about, but a great learning experience nonetheless. You can find my solution here.

:3rd_place_medal: (Bronze medal - 100th place - Top 7%) Repository for the "Jigsaw Multilingual Toxic Comment Classification" Kaggle competition. - dimitreOliveira/Jigsaw-Multilingual-Toxic-Comment-Classification

This dataset is a replica of the data released for the Jigsaw Toxic Comment Classification Challenge and Jigsaw Multilingual Toxic Comment Classification competition on Kaggle, with the test dataset merged with the test_labels released after the end of the competitions.

The dataset used in this project is the Toxic Comment Classification Challenge from Kaggle. The dataset contains approximately 159,000 comments from Wikipedia talk pages that have been labeled by human annotators as toxic or non-toxic.

Rank relative ratings of toxicity between comments

Jigsaw Comment Toxicity Classification Kaggle Competition · Repository: Repository: Paper: Paper: Leaderboard: Leaderboard: Point of Contact: Point of Contact: Total file size: 13.3 kB · Text Classification • Updated Nov 8, 2024 • 130k • • 75 · Updated Feb 19, 2025 • 53.7k • 3 ·

For each competition, we also provide grading scripts that can be used to evaluate the score of a submission. We use the Kaggle API to download the raw datasets. Ensure that you have downloaded your Kaggle credentials (kaggle.json) and placed it in the ~/.kaggle/ directory (this is the default location where the Kaggle API looks for your credentials).

December 7, 2025 - Weights & Biases, developer tools for machine learning

To Train Them Is My Cause, Chun Ming Lee. 1st place solution overview. https://www.kaggle.com/competitions/jigsaw-toxic-comment-classification-challenge/writeups/toxic-crusaders-1st-place-solution-overview.