---
title: "sentimentr (R package): papers citing this CRAN package"
description: "9 papers in the tracked journals link to sentimentr (R package) in their Crossref records, the first in 2019; most of them (2) in 2026."
url: https://scholar4ai.com/code/cran-sentimentr
markdown_url: https://scholar4ai.com/code/cran-sentimentr.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "9 papers in the tracked journals link to sentimentr (R package) in their Crossref records, the first in 2019; most of them (2) in 2026. (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)
---

# sentimentr (R package): papers linking to it

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

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

## Key findings

- 9 papers in the tracked journals link to sentimentr (R package) in their Crossref records, the first in 2019; most of them (2) in 2026.
- By category: Operations Research (3), Management (2) and Higher Education and Research (2); the journals with the most are Public Transport (2), Scientometrics (2) and Technological Forecasting and Social Change (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links sentimentr (R package).

## By year

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

| Year | Papers |
|---|---:|
| 2019 | 1 |
| 2021 | 1 |
| 2022 | 2 |
| 2023 | 2 |
| 2024 | 1 |
| 2026 | 2 |

## Journals

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

| Journal | Papers |
|---|---:|
| [Public Transport](https://scholar4ai.com/journals/public-transport.md) | 2 |
| [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | 2 |
| [Technological Forecasting and Social Change](https://scholar4ai.com/journals/technological-forecasting-and-social-change.md) | 1 |
| [Transportation Research Part A Policy and Practice](https://scholar4ai.com/journals/transportation-research-part-a-policy-and-practice.md) | 1 |
| [Financial Innovation](https://scholar4ai.com/journals/financial-innovation.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Decoding customer experiences in rail transport service: application of hybrid sentiment analysis](https://doi.org/10.1007/s12469-021-00289-7) (Public Transport, 2022)
  - [SentiHawkes: a sentiment-aware Hawkes point process to model service quality of public transport using Twitter data](https://doi.org/10.1007/s12469-022-00310-7) (Public Transport, 2023) — cites the paper above

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2021-02-28 | [Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach](https://doi.org/10.1016/j.jbusres.2021.02.028) | [Journal of Business Research](https://scholar4ai.com/journals/journal-of-business-research.md) | Arghya Ray, Pradip Kumar Bala, Nripendra Pratap Rana | 74 | cites it |
| 2019-08-12 | [The impact of host race and gender on prices on Airbnb](https://doi.org/10.1016/j.jhe.2019.101635) | [Journal of Housing Economics](https://scholar4ai.com/journals/journal-of-housing-economics.md) | Anya Marchenko | 38 | cites it |
| 2022-10-01 | [Is academic writing becoming more positive? A large-scale diachronic case study of Science research articles across 25 years](https://doi.org/10.1007/s11192-022-04515-2) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Zhou-min Yuan, Mingxin Yao | 33 | cites it |
| 2022-02-22 | [Decoding customer experiences in rail transport service: application of hybrid sentiment analysis](https://doi.org/10.1007/s12469-021-00289-7) | [Public Transport](https://scholar4ai.com/journals/public-transport.md) | Dibya Nandan Mishra, Rajeev Kumar Panda | 21 | cites it |
| 2024-09-12 | [Natural language processing for participatory corporate foresight: The participant input analyzer for identifying biases and fallacies](https://doi.org/10.1016/j.techfore.2024.123652) | [Technological Forecasting and Social Change](https://scholar4ai.com/journals/technological-forecasting-and-social-change.md) | Jörg M. Delhaes, Ana Vieira, Mónica Duarte Oliveira | 10 | cites it |
| 2023-04-20 | [SentiHawkes: a sentiment-aware Hawkes point process to model service quality of public transport using Twitter data](https://doi.org/10.1007/s12469-022-00310-7) | [Public Transport](https://scholar4ai.com/journals/public-transport.md) | Mohammad Masoud Rahimi, Elham Naghizade, Mark Stevenson et al. | 3 | cites it |
| 2023-01-22 | [Words matter: how ecologists discuss managed and non-managed bees and birds](https://doi.org/10.1007/s11192-022-04620-2) | [Scientometrics](https://scholar4ai.com/journals/scientometrics.md) | Magda P. Argueta-Guzmán, Mari West, Marília Palumbo Gaiarsa et al. | 0 | cites it |
| 2026-07-10 | [Investor emotions and fundraising performance of initial coin offerings: a lexicon based sentiment analysis of public tweets](https://doi.org/10.1186/s40854-026-00952-7) | [Financial Innovation](https://scholar4ai.com/journals/financial-innovation.md) | Nishanth Bhimireddy, Yannis Pierrakis, Riccardo Vecchiato | 0 | cites it |
| 2026-09-02 | [Ready to begin: driving towards the best and steering away from the worst in road pricing policy reform](https://doi.org/10.1016/j.tra.2026.105229) | [Transportation Research Part A Policy and Practice](https://scholar4ai.com/journals/transportation-research-part-a-policy-and-practice.md) | Matthew J. Beck, Michiel C.J. Bliemer, John Matthew Rose | 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). sentimentr (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-sentimentr

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