# LABR: A Large Scale Arabic Sentiment Analysis Benchmark

arXiv: https://arxiv.org/abs/1411.6718 · HTML: https://mlsanity.com/paper/1411.6718/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Nov 2014.

## Built on by (most cited first, 22 of 22)

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- [Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark](https://mlsanity.com/paper/2306.07902/) (2023)
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- [Assessment of Massively Multilingual Sentiment Classifiers](https://mlsanity.com/paper/2204.04937/) (2022)
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- [Arabic Sentiment Analysis with Noisy Deep Explainable Model](https://mlsanity.com/paper/2309.13731/) (2023)
- [A comprehensive survey of contemporary Arabic sentiment analysis: Methods, Challenges, and Future Directions](https://mlsanity.com/paper/2502.03827/) (2025)
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- [Understanding the Impact of Culture in Assessing Helpfulness of Online Reviews](https://mlsanity.com/paper/2305.04836/) (2023)
- [Arabic Text Sentiment Analysis: Reinforcing Human-Performed Surveys with Wider Topic Analysis](https://mlsanity.com/paper/2403.01921/) (2024)
- [From FusHa to Folk: Exploring Cross-Lingual Transfer in Arabic Language Models](https://mlsanity.com/paper/2602.09826/) (2026)
- [AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset](https://mlsanity.com/paper/2110.01948/) (2021)
- [A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets](https://mlsanity.com/paper/2201.12664/) (2022)
- [AlcLaM: Arabic Dialectal Language Model](https://mlsanity.com/paper/2407.13097/) (2024)
- [Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation](https://mlsanity.com/paper/2508.19966/) (2025)
- [Domain-Adaptive Pre-Training for Arabic Aspect-Based Sentiment Analysis: A Comparative Study of Domain Adaptation and Fine-Tuning Strategies](https://mlsanity.com/paper/2509.16788/) (2025)
- [MAPROC at AHaSIS Shared Task: Few-Shot and Sentence Transformer for Sentiment Analysis of Arabic Hotel Reviews](https://mlsanity.com/paper/2511.15291/) (2025)
- [Character Iconicity vs. Arbitrariness: An Arabic NLP Perspective](https://mlsanity.com/paper/2608.02935/) (2026)

## Abstract (arXiv)

We introduce LABR, the largest sentiment analysis dataset to-date for the Arabic language. It consists of over 63,000 book reviews, each rated on a scale of 1 to 5 stars. We investigate the properties of the dataset, and present its statistics. We explore using the dataset for two tasks: (1) sentiment polarity classification; and (2) ratings classification. Moreover, we provide standard splits of the dataset into training, validation and testing, for both polarity and ratings classification, in both balanced and unbalanced settings. We extend our previous work by performing a comprehensive analysis on the dataset. In particular, we perform an extended survey of the different classifiers typically used for the sentiment polarity classification problem. We also construct a sentiment lexicon from the dataset that contains both single and compound sentiment words and we explore its effectiveness. We make the dataset and experimental details publicly available.