---
title: "The graph-tool python library: papers citing this dataset"
description: "3 papers in the tracked journals link to the figshare dataset The graph-tool python library in their Crossref records, the first in 2022; most of them (1) in 2025."
url: https://scholar4ai.com/code/figshare-1164194
markdown_url: https://scholar4ai.com/code/figshare-1164194.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 figshare dataset The graph-tool python library in their Crossref records, the first in 2022; most of them (1) in 2025. (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)
---

# The graph-tool python library: papers linking to it

Research papers in the 480 tracked journals that link to The graph-tool python library (https://doi.org/10.6084/m9.figshare.1164194), 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.

- figshare
- Dataset
- 2017
- https://doi.org/10.6084/m9.figshare.1164194

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

## Key findings

- 3 papers in the tracked journals link to the figshare dataset The graph-tool python library in their Crossref records, the first in 2022; most of them (1) in 2025.
- By category: AI (2) and Operations Research (1); the journals with the most are Computational Optimization and Applications (1), Neural Computing and Applications (1) and Data Mining and Knowledge Discovery (1).

## By year

*Papers linking to The graph-tool python library by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2023 | 1 |
| 2025 | 1 |

## Journals

*Journals whose papers link to The graph-tool python library most*

| Journal | Papers |
|---|---:|
| [Computational Optimization and Applications](https://scholar4ai.com/journals/computational-optimization-and-applications.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | 1 |

## Papers

*Papers linking to The graph-tool python library, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-01-10 | [Synwalk: community detection via random walk modelling](https://doi.org/10.1007/s10618-021-00809-w) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Christian Toth, Denis Helić, Bernhard Claus Geiger | 30 | cites it |
| 2023-03-30 | [A graph-based superframework for mixture model estimation using EM: an analysis of US wholesale electricity markets](https://doi.org/10.1007/s00521-023-08468-2) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Carlo Mari, Cristiano Baldassari | 4 | cites it |
| 2025-02-05 | [Ultra-small world detection in networks: subgraphs with prescribed distance distributions](https://doi.org/10.1007/s10589-024-00640-1) | [Computational Optimization and Applications](https://scholar4ai.com/journals/computational-optimization-and-applications.md) | Alexander Veremyev, Vladimir L. Boginski, Eduardo L. Pasiliao et al. | 2 | 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). The graph-tool python library: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/figshare-1164194

```bibtex
@misc{scholar4ai-code-figshare-1164194,
  author = {{Scholar4AI}},
  title = {The graph-tool python library: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/figshare-1164194}},
  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/).