---
title: "Arturus/kaggle-web-traffic: papers citing it"
description: "3 papers in the tracked journals link to the GitHub repository Arturus/kaggle-web-traffic in their Crossref records, the first in 2020; most of them (1) in 2023."
url: https://scholar4ai.com/code/github-arturus-kaggle-web-traffic
markdown_url: https://scholar4ai.com/code/github-arturus-kaggle-web-traffic.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the GitHub repository Arturus/kaggle-web-traffic in their Crossref records, the first in 2020; most of them (1) in 2023. (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)
---

# Arturus/kaggle-web-traffic: papers linking to it

Research papers in the 480 tracked journals that link to Arturus/kaggle-web-traffic (https://github.com/Arturus/kaggle-web-traffic), 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.

- GitHub
- 1,850 stars
- 656 forks
- Jupyter Notebook
- license MIT
- created 2017
- https://github.com/Arturus/kaggle-web-traffic

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

## Key findings

- 3 papers in the tracked journals link to the GitHub repository Arturus/kaggle-web-traffic in their Crossref records, the first in 2020; most of them (1) in 2023.
- By category: AI (3); the journals with the most are Knowledge-Based Systems (1), Machine Learning (1) and Data Mining and Knowledge Discovery (1).

## By year

*Papers linking to Arturus/kaggle-web-traffic by publication year*

| Year | Papers |
|---|---:|
| 2020 | 1 |
| 2022 | 1 |
| 2023 | 1 |

## Journals

*Journals whose papers link to Arturus/kaggle-web-traffic most*

| Journal | Papers |
|---|---:|
| [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 1 |
| [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 1 |
| [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | 1 |

## Papers

*Papers linking to Arturus/kaggle-web-traffic, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-12-02 | [Forecast evaluation for data scientists: common pitfalls and best practices](https://doi.org/10.1007/s10618-022-00894-5) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Hansika Hewamalage, Klaus Ackermann, Christoph Bergmeir | 296 | cites it |
| 2023-03-13 | [SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting](https://doi.org/10.1007/s10994-023-06316-x) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Rakshitha Godahewa, Geoffrey I. Webb, Daniel Francis Schmidt et al. | 15 | cites it |
| 2020-04-23 | [Hybrid time-aligned and context attention for time series prediction](https://doi.org/10.1016/j.knosys.2020.105937) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Zhumei Wang, Liang Zhang, Zhiming Ding | 8 | 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). Arturus/kaggle-web-traffic: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-arturus-kaggle-web-traffic

```bibtex
@misc{scholar4ai-code-github-arturus-kaggle-web-traffic,
  author = {{Scholar4AI}},
  title = {Arturus/kaggle-web-traffic: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-arturus-kaggle-web-traffic}},
  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/).