tashaphyne (Python package): papers linking to it

← Code and data repositories cited in research papers

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.

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#

20182021

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	2
Artificial Intelligence Review	1
Information Processing & Management	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Emotion analysis of Arabic tweets using deep learning approach 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 Journal Of Big Data, 2021 — cites the paper above

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	Information Processing & Management	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	Journal Of Big Data	Massa Baali, Nada Ghneim	68	cites it
2020-04-15	Empirical evaluation and study of text stemming algorithms	Artificial Intelligence Review	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	Journal Of Big Data	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

@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}
}

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