---
title: "Thematic Dispersion in Arabic Applied — Eddakrouri 2025"
description: "The paper measures how concentrated or spread out recent research on Arabic Applied Linguistics is across its subfields."
authors: ["Ayman Eddakrouri", "Amani Ramadan"]
year: 2025
venue: "arXiv:2512.15328"
source: "https://arxiv.org/abs/2512.15328"
doi: "10.48550/arxiv.2512.15328"
arxiv: "2512.15328"
licence: "CC BY 4.0 (arXiv)"
licence_url: "http://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/eddakrouri-2025-thematic-dispersion-arabic-applied-linguistics/"
---
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# Thematic Dispersion in Arabic Applied Linguistics: A Bibliometric Analysis using Brookes' Measure

**Authors:** Ayman Eddakrouri, Amani Ramadan · **Year:** 2025 · **Venue:** arXiv:2512.15328 · **Licence:** [CC BY 4.0 (arXiv)](http://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://arxiv.org/abs/2512.15328) · [PDF](https://arxiv.org/pdf/2512.15328) · [DOI 10.48550/arxiv.2512.15328](https://doi.org/10.48550/arxiv.2512.15328) · [arXiv 2512.15328](https://arxiv.org/abs/2512.15328) · [OpenAlex](https://openalex.org/W7116079380)

**Citations:** 0 citations (openalex-snapshot · 2026-10-14)

## Summary
The paper measures how concentrated or spread out recent research on Arabic Applied Linguistics is across its subfields. From Scopus, the authors gathered publications from 2019–2025 using a Boolean query. They screened the results by hand and placed each of 1,564 papers into exactly one of eight sub-disciplines, checking coding consistency with a second rater. They then computed Brookes' Measure of Categorical Dispersion, Δ = (M − 1)/(N − 1). N is the number of categories and M is the frequency-weighted mean rank, where the largest category gets rank 1 and ties share an averaged rank. The result is Δ = 0.194, which the authors read as strong dispersion. Computational Linguistics leads, but Sociolinguistics, Language Teaching and other subfields remain substantial. The authors attribute this pluralism to the complexity of Arabic: diglossia, dialect variety, a distinctive script and rich morphology. They also position the work as a reusable template for applying Brookes' formula. Readers should note that the paper's description of the extremes (which M gives Δ = 0 or 1) and of the direction in which the long tail moves M does not fit cleanly with its stated ranking rule. The concluding restatement of the formula also contains a typo.

## Key points
- The dataset has 1,564 Scopus-indexed publications from 2019–2025, manually cleaned of false positives, non-linguistics papers and duplicates.
- The eight mutually exclusive categories are:
  - Computational Linguistics/NLP
  - Sociolinguistics
  - Language Teaching
  - Discourse Analysis
  - SLA
  - Applied Linguistics (General)
  - Corpus Linguistics
  - Language Assessment
- A second rater independently recoded a stratified 15% sample (about 235 papers), giving Cohen's κ = 0.87.
- The measured value is Δ = 0.194. The four smallest categories (SLA, Corpus, General, Assessment) form a long tail of roughly 13% of output.
- Δ is proposed as a baseline for later windows such as 2026–2032, for comparison with other fields, and as guidance for editors, funders and students.

## Interesting ideas
- A single normalized number divided by (N − 1) summarizes how evenly items fall into categories, so distributions with different category counts and corpus sizes can be compared. — For Mova (learn): Compute such a dispersion score over deprels, frame types or error classes in each silver batch, so we can spot when a corpus or a failure profile is collapsing onto a few categories.
- Reliability is checked by double-coding a stratified random slice and reporting Cohen's κ, rather than trusting a single annotator. — For Mova (learn): Apply κ on a stratified sample to agreement between witness parsers or LLM teacher tiers. This gives a quantitative gate before labels enter silver data.
- The coding scheme uses mutually exclusive categories with short operational definitions, plus an explicit catch-all for items that do not fit. — For Mova (frames): Speech-act or frame inventories could follow this pattern, giving every label a one-line operational test and a visible "other" bin. Tracking that bin shows where the inventory needs extending.
- Tied frequencies get the average of the ranks they span, so ordering stays well defined when counts are equal. — For Mova (answer): Rank-based scoring of candidate answers or readings could use averaged ranks for ties. This avoids arbitrary tie-breaking that is hard to explain.
- The paper's own explanation of which extreme gives Δ = 0 or 1 does not match its stated ranking rule, which shows the value of testing a metric on boundary cases. — For Mova (learn): Every new evaluation metric should ship with tiny synthetic extreme cases (all in one class, perfectly uniform) as negative controls. These confirm that the metric moves in the intended direction.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{eddakrouri2025thematic,
  title = {{Thematic Dispersion in Arabic Applied Linguistics: A Bibliometric Analysis using Brookes' Measure}},
  author = {Eddakrouri, Ayman and Ramadan, Amani},
  year = {2025},
  doi = {10.48550/arxiv.2512.15328},
  eprint = {2512.15328},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2512.15328}
}
```

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## References

16 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Abdullah, M. R., Talib, N. H., Zulkifli, M. F., Muhayudin, A. A., Abdallah, A. S., & Yaakob, K. M. (2025). A bibliometric analysis of scientific output in the field of Arabic Language: Trends and research developments from 2005 to 2024. International Journal of Modern Education, 7(26). doi:https://doi.org/10.35631/IJMOE.726028 [↗](https://doi.org/10.35631/ijmoe.726028)
2. Albirini, A. (2016). Modern Arabic Sociolinguistics: Diglossia, variation, codeswitching, attitudes and identity. London: Routledge. doi:https://doi.org/10.4324/9781315683737 [↗](https://doi.org/10.4324/9781315683737)
3. Al-Kharashi, I., Alsubait, T., & Alahmadi, T. (2022). Challenges in Arabic Natural Language Processing: A Survey. International Journal of Artificial Intelligence and Applications, 13(2), 15–28. [find](https://scholar.google.com/scholar?q=Al%2DKharashi%2C+I%2E%2C+Alsubait%2C+T%2E%2C+%26+Alahmadi%2C+T%2E+%282022%29%2E+Challenges+in+Arabic+Natural+Language+Processing%3A+A+Survey%2E+International+Journal+of+Artificial+Intelligence+and+Applications%2C+13%282%29%2C+15%E2%80%9328%2E)
4. Brookes, B. C. (1977). A measure of categorical dispersion. The Information Scientist, 11(1), 11-17. [find](https://scholar.google.com/scholar?q=Brookes%2C+B%2E+C%2E+%281977%29%2E+A+measure+of+categorical+dispersion%2E+The+Information+Scientist%2C+11%281%29%2C+11%2D17%2E)
5. Cohen, J. A. (1960). A coefficient of agreement for nominal scales. Educ. Psychol. Meas., 20, 37-46. [find](https://scholar.google.com/scholar?q=Cohen%2C+J%2E+A%2E+%281960%29%2E+A+coefficient+of+agreement+for+nominal+scales%2E+Educ%2E+Psychol%2E+Meas%2E%2C+20%2C+37%2D46%2E)
6. Gini, C. (1955). Variabilità e mutabilità. In e. E. Pizetti and T.Salvemini, Memorie di Metodologica Statistica. Rome: Libreria Eredi Virgilio Veschi. [find](https://scholar.google.com/scholar?q=Gini%2C+C%2E+%281955%29%2E+Variabilit%C3%A0+e+mutabilit%C3%A0%2E+In+e%2E+E%2E+Pizetti+and+T%2ESalvemini%2C+Memorie+di+Metodologica+Statistica%2E+Rome%3A+Libreria+Eredi+Virgilio+Veschi%2E)
7. Hirschman, A. O. (September 1964). The Paternity of an Index. American Economic Review, 761-62. [find](https://scholar.google.com/scholar?q=Hirschman%2C+A%2E+O%2E+%28September+1964%29%2E+The+Paternity+of+an+Index%2E+American+Economic+Review%2C+761%2D62%2E)
8. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159-174. [find](https://scholar.google.com/scholar?q=Landis%2C+J%2E+R%2E%2C+%26+Koch%2C+G%2E+G%2E+%281977%29%2E+The+measurement+of+observer+agreement+for+categorical+data%2E+Biometrics%2C+33%2C+159%2D174%2E)
9. Leydesdorff, L., & Bornmann, L. (2016). The operationalization of “fields” as WoS subject categories (WCs) in evaluative bibliometrics: The cases of “library and information science” and “science & technology studies”. Journal of the Association for Information Science and Technology, 67(3), 707-714. doi:https://doi.org/10.1002/asi.23408 [↗](https://doi.org/10.1002/asi.23408)
10. Leydesdorff, L., & Rafols, I. (2011). Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations. Journal of Informetrics, 5(1), 87-100. doi:[https://www.sciencedirect.com/science/article/abs/pii/S1751157710000854](https://www.sciencedirect.com/science/article/abs/pii/S1751157710000854) [↗](https://www.sciencedirect.com/science/article/abs/pii/S1751157710000854)
11. Lorenz, M. O. (1905). Methods of measuring the concentration of wealth. J. Amer. Statist. Assoc., 209–219. [find](https://scholar.google.com/scholar?q=Lorenz%2C+M%2E+O%2E+%281905%29%2E+Methods+of+measuring+the+concentration+of+wealth%2E+J%2E+Amer%2E+Statist%2E+Assoc%2E%2C+209%E2%80%93219%2E)
12. McHugh, M. L. (2012). Interrater reliability: The kappa statistic. 22(3), 276–282. doi:https://doi.org/10.11613/BM.2012.031 [↗](https://doi.org/10.11613/bm.2012.031)
13. Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics, 106, 213–228. doi:https://link.springer.com/article/10.1007/s11192-015-1765-5 [↗](https://doi.org/10.1007/s11192-015-1765-5)
14. Schmitt, N., & Celce-Murcia, M. (2002). An overview of applied linguistics. In N. Schmitt, An introduction to applied linguistics (pp. 1-16). London: Arnold. [find](https://scholar.google.com/scholar?q=Schmitt%2C+N%2E%2C+%26+Celce%2DMurcia%2C+M%2E+%282002%29%2E+An+overview+of+applied+linguistics%2E+In+N%2E+Schmitt%2C+An+introduction+to+applied+linguistics+%28pp%2E+1%2D16%29%2E+London%3A+Arnold%2E)
15. Wahba, K. M., England, L., & Taha, Z. A. (Eds.). (2018). Handbook for Arabic Language Teaching Professionals in the 21st Century. New York: Routledge. doi:https://doi.org/10.4324/9781315676111 [↗](https://doi.org/10.4324/9781315676111)
16. Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. doi:https://doi.org/10.1177/1094428114562629 [↗](https://doi.org/10.1177/1094428114562629)