readr (R package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to readr (R package) (https://CRAN.R-project.org/package=readr), 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#

5 papers in the tracked journals link to readr (R package) in their Crossref records, the first in 2018; most of them (2) in 2020.
By category: AI (3), Marketing (1) and Management (1); the journals with the most are Journal of Marketing Analytics (1), Neural Computing and Applications (1) and Data Mining and Knowledge Discovery (1).

By year#

20182025

Papers linking to readr (R package) by publication year
Year	Papers
2018	1
2020	2
2023	1
2025	1

Journals#

Journals whose papers link to readr (R package) most
Journal	Papers
Journal of Marketing Analytics	1
Neural Computing and Applications	1
Data Mining and Knowledge Discovery	1
The Leadership Quarterly	1
Expert Systems with Applications	1

Papers linking to readr (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2020-07-06	Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms	Neural Computing and Applications	Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis	177	cites it
2018-12-27	Inducing non-orthogonal and non-linear decision boundaries in decision trees via interactive basis functions	Expert Systems with Applications	Antonio Páez, Fernando A. López Hernández, Manuel Ruiz Marín et al.	20	cites it
2025-04-24	Does expressing uncertainty help or harm leaders?	The Leadership Quarterly	Shilaan Alzahawi, Francis J. Flynn	9	cites it
2023-11-03	Marketing analytics with RStudio: a software review	Journal of Marketing Analytics	David Dege, Philipp Brüggemann	8	cites it
2020-03-16	ptype: probabilistic type inference	Data Mining and Knowledge Discovery	Taha Ceritli, Christopher K. I. Williams, James Geddes	5	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). readr (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-readr

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

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).