The graph-tool python library: papers linking to it

figshare · Dataset · 2017 · doi.org/10.6084/m9.figshare.1164194

← Code and data repositories cited in research papers

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.

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#

20222025

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	1
Neural Computing and Applications	1
Data Mining and Knowledge Discovery	1

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	Data Mining and Knowledge Discovery	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	Neural Computing and Applications	Carlo Mari, Cristiano Baldassari	4	cites it
2025-02-05	Ultra-small world detection in networks: subgraphs with prescribed distance distributions	Computational Optimization and Applications	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

@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}
}

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