# Ensemble of pre-trained language models and data augmentation for hate speech detection from Arabic tweets

arXiv: https://arxiv.org/abs/2407.02448 · HTML: https://mlsanity.com/paper/2407.02448/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 52 references that are in the map.
- First posted on arXiv 2 Jul 2024.

## Builds on (most cited first, 16 of 16)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [How to Fine-Tune BERT for Text Classification?](https://mlsanity.com/paper/1905.05583/) (2019)
- [AraBERT: Transformer-based Model for Arabic Language Understanding](https://mlsanity.com/paper/2003.00104/) (2020)
- [Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior](https://mlsanity.com/paper/1802.00393/) (2018)
- [ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic](https://mlsanity.com/paper/2101.01785/) (2020)
- [Multilingual and Multi-Aspect Hate Speech Analysis](https://mlsanity.com/paper/1908.11049/) (2019)
- [AraELECTRA: Pre-Training Text Discriminators for Arabic Language Understanding](https://mlsanity.com/paper/2012.15516/) (2020)
- [Arabic Offensive Language on Twitter: Analysis and Experiments](https://mlsanity.com/paper/2004.02192/) (2020)
- [OSACT4 Shared Task on Offensive Language Detection: Intensive Preprocessing-Based Approach](https://mlsanity.com/paper/2005.07297/) (2020)
- [Leveraging Affective Bidirectional Transformers for Offensive Language Detection](https://mlsanity.com/paper/2006.01266/) (2020)
- [Enhanced Offensive Language Detection Through Data Augmentation](https://mlsanity.com/paper/2012.02954/) (2020)
- [SalamNET at SemEval-2020 Task12: Deep Learning Approach for Arabic Offensive Language Detection](https://mlsanity.com/paper/2007.13974/) (2020)
- [Arabic Offensive Language Detection Using Machine Learning and Ensemble Machine Learning Approaches](https://mlsanity.com/paper/2005.08946/) (2020)
- [Transfer Learning Approach for Arabic Offensive Language Detection System -- BERT-Based Model](https://mlsanity.com/paper/2102.05708/) (2021)
- [Effect of Word Embedding Models on Hate and Offensive Speech Detection](https://mlsanity.com/paper/2012.07534/) (2020)

## Built on by (most cited first, 1 of 1)

- [Toward Generalized Cross-Lingual Hateful Language Detection with Web-Scale Data and Ensemble LLM Annotations](https://mlsanity.com/paper/2604.09625/) (2026)

## Abstract (arXiv)

Today, hate speech classification from Arabic tweets has drawn the attention of several researchers. Many systems and techniques have been developed to resolve this classification task. Nevertheless, two of the major challenges faced in this context are the limited performance and the problem of imbalanced data. In this study, we propose a novel approach that leverages ensemble learning and semi-supervised learning based on previously manually labeled. We conducted experiments on a benchmark dataset by classifying Arabic tweets into 5 distinct classes: non-hate, general hate, racial, religious, or sexism. Experimental results show that: (1) ensemble learning based on pre-trained language models outperforms existing related works; (2) Our proposed data augmentation improves the accuracy results of hate speech detection from Arabic tweets and outperforms existing related works. Our main contribution is the achievement of encouraging results in Arabic hate speech detection.