---
title: "tashaphyne (Python package): papers citing it"
description: "4 papers in the tracked journals link to tashaphyne (Python package) in their Crossref records, the first in 2018; most of them (1) in 2021."
url: https://scholar4ai.com/code/pypi-tashaphyne
markdown_url: https://scholar4ai.com/code/pypi-tashaphyne.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "4 papers in the tracked journals link to tashaphyne (Python package) in their Crossref records, the first in 2018; most of them (1) in 2021. (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)
---

# tashaphyne (Python package): papers linking to it

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

- PyPI
- https://pypi.org/project/tashaphyne/

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

## Key findings

- 4 papers in the tracked journals link to tashaphyne (Python package) in their Crossref records, the first in 2018; most of them (1) in 2021.
- By category: AI (4); the journals with the most are Journal Of Big Data (2), Artificial Intelligence Review (1) and Information Processing & Management (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links tashaphyne (Python package).

## By year

*Papers linking to tashaphyne (Python package) by publication year*

| Year | Papers |
|---|---:|
| 2018 | 1 |
| 2019 | 1 |
| 2020 | 1 |
| 2021 | 1 |

## Journals

*Journals whose papers link to tashaphyne (Python package) most*

| Journal | Papers |
|---|---:|
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 2 |
| [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 1 |
| [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Emotion analysis of Arabic tweets using deep learning approach](https://doi.org/10.1186/s40537-019-0252-x) (Journal Of Big Data, 2019)
  - [Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media](https://doi.org/10.1186/s40537-021-00488-w) (Journal Of Big Data, 2021) — cites the paper above

## Papers

*Papers linking to tashaphyne (Python package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2018-09-07 | [A comprehensive survey of arabic sentiment analysis](https://doi.org/10.1016/j.ipm.2018.07.006) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | Mahmoud Al‐Ayyoub, Abed Allah Khamaiseh, Yaser Jararweh et al. | 200 | cites it |
| 2019-10-16 | [Emotion analysis of Arabic tweets using deep learning approach](https://doi.org/10.1186/s40537-019-0252-x) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Massa Baali, Nada Ghneim | 68 | cites it |
| 2020-04-15 | [Empirical evaluation and study of text stemming algorithms](https://doi.org/10.1007/s10462-020-09828-3) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Abdul Jabbar, Sajid Iqbal, Manzoor Illahi Tamimy et al. | 49 | cites it |
| 2021-07-02 | [Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media](https://doi.org/10.1186/s40537-021-00488-w) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Yahya Albalawi, Jim Buckley, Nikola S. Nikolov | 42 | 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). tashaphyne (Python package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/pypi-tashaphyne

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