# Arabic natural language processing: An overview

arXiv: https://arxiv.org/abs/1903.02784 · HTML: https://mlsanity.com/paper/1903.02784/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Mar 2019.

## Built on by (most cited first, 20 of 20)

- [Masader: Metadata Sourcing for Arabic Text and Speech Data Resources](https://mlsanity.com/paper/2110.06744/) (2021)
- [A Survey of Corpora for Germanic Low-Resource Languages and Dialects](https://mlsanity.com/paper/2304.09805/) (2023)
- [Masader Plus: A New Interface for Exploring +500 Arabic NLP Datasets](https://mlsanity.com/paper/2208.00932/) (2022)
- [A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends](https://mlsanity.com/paper/2302.03512/) (2023)
- [AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://mlsanity.com/paper/2306.06800/) (2023)
- [Prediction of Arabic Legal Rulings using Large Language Models](https://mlsanity.com/paper/2310.10260/) (2023)
- [Sexism detection: The first corpus in Algerian dialect with a code-switching in Arabic/ French and English](https://mlsanity.com/paper/2104.01443/) (2021)
- [Evaluation of Semantic Search and its Role in Retrieved-Augmented-Generation (RAG) for Arabic Language](https://mlsanity.com/paper/2403.18350/) (2024)
- [Dialect Identification in Nuanced Arabic Tweets Using Farasa Segmentation and AraBERT](https://mlsanity.com/paper/2102.09749/) (2021)
- [sarcasm detection and quantification in arabic tweets](https://mlsanity.com/paper/2108.01425/) (2021)
- [Evaluating the Effectiveness of the Foundational Models for Q&A Classification in Mental Health care](https://mlsanity.com/paper/2406.15966/) (2024)
- [A Systematic Survey of Natural Language Processing for the Greek Language](https://mlsanity.com/paper/2407.09861/) (2024)
- [A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation](https://mlsanity.com/paper/2606.25476/) (2026)
- [Universal Language Modelling agent](https://mlsanity.com/paper/2306.06521/) (2023)
- [Dotless Representation of Arabic Text: Analysis and Modeling](https://mlsanity.com/paper/2312.16104/) (2023)
- [PersianRAG: A Retrieval-Augmented Generation System for Persian Language](https://mlsanity.com/paper/2411.02832/) (2024)
- [An Exploration of Knowledge Editing for Arabic](https://mlsanity.com/paper/2507.09629/) (2025)
- [AutoArabic: A Three-Stage Framework for Localizing Video-Text Retrieval Benchmarks](https://mlsanity.com/paper/2509.16438/) (2025)
- [Saar-Voice: A Multi-Speaker Saarbr"ucken Dialect Speech Corpus](https://mlsanity.com/paper/2604.11803/) (2026)
- [A Comprehensive Analysis of Arabic Natural Language Processing Research: Trends, Topic Evolution, and Research Gaps -- A Bibliometric and Topic-Based Study](https://mlsanity.com/paper/2608.23421/) (2026)

## Abstract (arXiv)

Arabic is recognised as the 4th most used language of the Internet. Arabic has three main varieties: (1) classical Arabic (CA), (2) Modern Standard Arabic (MSA), (3) Arabic Dialect (AD). MSA and AD could be written either in Arabic or in Roman script (Arabizi), which corresponds to Arabic written with Latin letters, numerals and punctuation. Due to the complexity of this language and the number of corresponding challenges for NLP, many surveys have been conducted, in order to synthesise the work done on Arabic. However these surveys principally focus on two varieties of Arabic (MSA and AD, written in Arabic letters only), they are slightly old (no such survey since 2015) and therefore do not cover recent resources and tools. To bridge the gap, we propose a survey focusing on 90 recent research papers (74% of which were published after 2015). Our study presents and classifies the work done on the three varieties of Arabic, by concentrating on both Arabic and Arabizi, and associates each work to its publicly available resources whenever available.