textstat (Python package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to textstat (Python package) (https://pypi.org/project/textstat/), 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#

4 papers in the tracked journals link to textstat (Python package) in their Crossref records, the first in 2018; most of them (1) in 2026.
By category: Higher Education and Research (2), Finance (1) and Information Systems (1); the journals with the most are Scientometrics (2), The Geneva Papers on Risk and Insurance Issues and Practice (1) and Electronic Commerce Research and Applications (1).

By year#

20182026

Papers linking to textstat (Python package) by publication year
Year	Papers
2018	1
2021	1
2025	1
2026	1

Journals#

Journals whose papers link to textstat (Python package) most
Journal	Papers
Scientometrics	2
The Geneva Papers on Risk and Insurance Issues and Practice	1
Electronic Commerce Research and Applications	1

Papers linking to textstat (Python package), most cited first
Published	Title	Journal	Authors	Citations	Link
2021-03-31	Using a hybrid content-based and behaviour-based featuring approach in a parallel environment to detect fake reviews	Electronic Commerce Research and Applications	Gregorius Satia Budhi, Raymond Chiong, Zuli Wang et al.	49	cites it
2018-07-04	Citance-based retrieval and summarization using IR and machine learning	Scientometrics	Samaneh Karimi, Luis F. T. Moraes, Avisha Das et al.	13	cites it
2025-09-07	Dynamic optimization of peer review length using information density analysis	Scientometrics	Prabhat Kumar Bharti, Tirath Bhathawala	0	cites it
2026-07-22	Cyber risk reporting in German listed enterprises: a textual analysis of disclosure informativeness	The Geneva Papers on Risk and Insurance Issues and Practice	Alina Salzberger, Felix Hausruckinger	0	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). textstat (Python package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/pypi-textstat

@misc{scholar4ai-code-pypi-textstat,
  author = {{Scholar4AI}},
  title = {textstat (Python package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/pypi-textstat}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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