# A review of sentiment analysis research in Arabic language

arXiv: https://arxiv.org/abs/2005.12240 · HTML: https://mlsanity.com/paper/2005.12240/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2020.

## Built on by (most cited first, 9 of 9)

- [Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language](https://mlsanity.com/paper/2106.12488/) (2021)
- [Arabic Sentiment Analysis with Noisy Deep Explainable Model](https://mlsanity.com/paper/2309.13731/) (2023)
- [Arabic Fake News Detection Based on Deep Contextualized Embedding Models](https://mlsanity.com/paper/2205.03114/) (2022)
- [Ensembling Multilingual Transformers for Robust Sentiment Analysis of Tweets](https://mlsanity.com/paper/2509.24080/) (2025)
- [Overview of the Arabic Sentiment Analysis 2021 Competition at KAUST](https://mlsanity.com/paper/2109.14456/) (2021)
- [A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets](https://mlsanity.com/paper/2201.12664/) (2022)
- [UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis](https://mlsanity.com/paper/2306.01093/) (2023)
- [Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation](https://mlsanity.com/paper/2508.19966/) (2025)
- [Algerian Dialect](https://mlsanity.com/paper/2512.19543/) (2025)

## Abstract (arXiv)

Sentiment analysis is a task of natural language processing which has recently attracted increasing attention. However, sentiment analysis research has mainly been carried out for the English language. Although Arabic is ramping up as one of the most used languages on the Internet, only a few studies have focused on Arabic sentiment analysis so far. In this paper, we carry out an in-depth qualitative study of the most important research works in this context by presenting limits and strengths of existing approaches. In particular, we survey both approaches that leverage machine translation or transfer learning to adapt English resources to Arabic and approaches that stem directly from the Arabic language.