---
title: "jigsaw-toxic-comment-classification-challenge"
description: "6 papers in the tracked journals link to the Kaggle dataset jigsaw-toxic-comment-classification-challenge in their Crossref records, the first in 2021; most of them (2) in 2024."
url: https://scholar4ai.com/code/kaggle-competition-jigsaw-toxic-comment-classification-challenge
markdown_url: https://scholar4ai.com/code/kaggle-competition-jigsaw-toxic-comment-classification-challenge.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "6 papers in the tracked journals link to the Kaggle dataset jigsaw-toxic-comment-classification-challenge in their Crossref records, the first in 2021; most of them (2) in 2024. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# jigsaw-toxic-comment-classification-challenge: papers linking to it

Research papers in the 480 tracked journals that link to jigsaw-toxic-comment-classification-challenge (https://www.kaggle.com/competitions/jigsaw-toxic-comment-classification-challenge), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- Kaggle
- https://www.kaggle.com/competitions/jigsaw-toxic-comment-classification-challenge

All repositories: https://scholar4ai.com/code.md

## Key findings

- 6 papers in the tracked journals link to the Kaggle dataset jigsaw-toxic-comment-classification-challenge in their Crossref records, the first in 2021; most of them (2) in 2024.
- By category: AI (4) and Information Systems (2); the journals with the most are Knowledge-Based Systems (2), Information & Management (1) and Applied Intelligence (1).

## By year

*Papers linking to jigsaw-toxic-comment-classification-challenge by publication year*

| Year | Papers |
|---|---:|
| 2021 | 1 |
| 2023 | 1 |
| 2024 | 2 |
| 2025 | 1 |
| 2026 | 1 |

## Journals

*Journals whose papers link to jigsaw-toxic-comment-classification-challenge most*

| Journal | Papers |
|---|---:|
| [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2 |
| [Information & Management](https://scholar4ai.com/journals/information-management.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Language Resources and Evaluation](https://scholar4ai.com/journals/language-resources-and-evaluation.md) | 1 |
| [Information Systems Frontiers](https://scholar4ai.com/journals/information-systems-frontiers.md) | 1 |

## Papers

*Papers linking to jigsaw-toxic-comment-classification-challenge, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2023-10-21 | [Beyond plain toxic: building datasets for detection of flammable topics and inappropriate statements](https://doi.org/10.1007/s10579-023-09682-z) | [Language Resources and Evaluation](https://scholar4ai.com/journals/language-resources-and-evaluation.md) | Nikolay Babakov, Varvara Logacheva, Alexander Panchenko | 8 | cites it |
| 2024-09-24 | [Combating Online Malicious Behavior: Integrating Machine Learning and Deep Learning Methods for Harmful News and Toxic Comments](https://doi.org/10.1007/s10796-024-10540-8) | [Information Systems Frontiers](https://scholar4ai.com/journals/information-systems-frontiers.md) | Szu‐Yin Lin, Shih-Yi James Chien, Yi-Zhen Chen et al. | 6 | cites it |
| 2021-07-08 | [Learning product representations for generating reviews for cold products](https://doi.org/10.1016/j.knosys.2021.107282) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Fatemeh Pourgholamali, Mohsen Kahani, Zeinab Noorian et al. | 5 | cites it |
| 2024-04-01 | [MODE: a multimodal open-domain dialogue dataset with explanation](https://doi.org/10.1007/s10489-024-05479-x) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Hang Yin, Pinren Lu, Ziang Li et al. | 3 | cites it |
| 2025-04-24 | [Stylometric characteristics of code-switched offensive language in social media](https://doi.org/10.1016/j.im.2025.104153) | [Information & Management](https://scholar4ai.com/journals/information-management.md) | Lina Zhou, Zhe Fu | 3 | cites it |
| 2026-03-07 | [PPO-CIS : A deep reinforcement learning framework for real-time toxicity detection in social media](https://doi.org/10.1016/j.knosys.2026.115704) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Arezo Bodaghi, Benjamin C. M. Fung, Ketra Schmitt | 1 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). jigsaw-toxic-comment-classification-challenge: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-jigsaw-toxic-comment-classification-challenge

```bibtex
@misc{scholar4ai-code-kaggle-competition-jigsaw-toxic-comment-classification-challenge,
  author = {{Scholar4AI}},
  title = {jigsaw-toxic-comment-classification-challenge: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-competition-jigsaw-toxic-comment-classification-challenge}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).