---
title: "rvest (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to rvest (R package) in their Crossref records, the first in 2020; most of them (3) in 2020."
url: https://scholar4ai.com/code/cran-rvest
markdown_url: https://scholar4ai.com/code/cran-rvest.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to rvest (R package) in their Crossref records, the first in 2020; most of them (3) in 2020. (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)
---

# rvest (R package): papers linking to it

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

- CRAN
- https://CRAN.R-project.org/package=rvest

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

## Key findings

- 5 papers in the tracked journals link to rvest (R package) in their Crossref records, the first in 2020; most of them (3) in 2020.
- By category: Higher Education and Research (2), AI (2) and Operations Research (1); the journals with the most are Scientometrics (2), Expert Systems with Applications (2) and Computational Management Science (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links rvest (R package).

## By year

*Papers linking to rvest (R package) by publication year*

| Year | Papers |
|---|---:|
| 2020 | 3 |
| 2022 | 1 |
| 2023 | 1 |

## Journals

*Journals whose papers link to rvest (R package) most*

| Journal | Papers |
|---|---:|
| [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 2 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| [Computational Management Science](https://scholar4ai.com/journals/computational-management-science.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [An analytical system for evaluating academia units based on metrics provided by academic social network](https://doi.org/10.1016/j.eswa.2020.113608) (Expert Systems with Applications, 2020)
  - [Academic social networks metrics: an effective indicator for university performance?](https://doi.org/10.1007/s11192-021-04258-6) (Scientometrics, 2022) — cites the paper above

## Papers

*Papers linking to rvest (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-06-29 | [Emerging technologies and industrial leadership. A Wikipedia-based strategic analysis of Industry 4.0](https://doi.org/10.1016/j.eswa.2020.113645) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Andrea J. Bonaccorsi, Filippo Chiarello, Gualtiero Fantoni et al. | 34 | cites it |
| 2022-01-27 | [Academic social networks metrics: an effective indicator for university performance?](https://doi.org/10.1007/s11192-021-04258-6) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Łukasz Wiechetek, Zbigniew Pastuszak | 27 | cites it |
| 2023-04-25 | [Impact of public news sentiment on stock market index return and volatility](https://doi.org/10.1007/s10287-023-00454-2) | [Computational Management Science](https://scholar4ai.com/journals/computational-management-science.md) | Gianluca Anese, Marco Corazza, Michele Costola et al. | 20 | cites it |
| 2020-06-04 | [An analytical system for evaluating academia units based on metrics provided by academic social network](https://doi.org/10.1016/j.eswa.2020.113608) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Łukasz Wiechetek, Kongkiti Phusavat, Zbigniew Pastuszak | 14 | cites it |
| 2020-03-14 | [An exploration of gender gap using advanced data science tools: actuarial research community](https://doi.org/10.1007/s11192-020-03412-w) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Mengyu Yu, Mazie Krehbiel, Samantha Thompson et al. | 4 | 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). rvest (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-rvest

```bibtex
@misc{scholar4ai-code-cran-rvest,
  author = {{Scholar4AI}},
  title = {rvest (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-rvest}},
  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/).