# A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages

arXiv: https://arxiv.org/abs/2411.19017 · HTML: https://mlsanity.com/paper/2411.19017/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 52 of its 150 references that are in the map.
- First posted on arXiv 28 Nov 2024.

## Builds on (most cited first, 30 of 52)

- [Automated Hate Speech Detection and the Problem of Offensive Language](https://mlsanity.com/paper/1703.04009/) (2017)
- [The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes](https://mlsanity.com/paper/2005.04790/) (2020)
- [HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection](https://mlsanity.com/paper/2012.10289/) (2020)
- [Predicting the Type and Target of Offensive Posts in Social Media](https://mlsanity.com/paper/1902.09666/) (2019)
- [HateCheck: Functional Tests for Hate Speech Detection Models](https://mlsanity.com/paper/2012.15606/) (2020)
- [HateBERT: Retraining BERT for Abusive Language Detection in English](https://mlsanity.com/paper/2010.12472/) (2020)
- [SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)](https://mlsanity.com/paper/2006.07235/) (2020)
- [Multilingual and Multi-Aspect Hate Speech Analysis](https://mlsanity.com/paper/1908.11049/) (2019)
- [A Benchmark Dataset for Learning to Intervene in Online Hate Speech](https://mlsanity.com/paper/1909.04251/) (2019)
- [CONAN -- COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech](https://mlsanity.com/paper/1910.03270/) (2019)
- [Exploring Hate Speech Detection in Multimodal Publications](https://mlsanity.com/paper/1910.03814/) (2019)
- [Measuring the Reliability of Hate Speech Annotations: The Case of the European Refugee Crisis](https://mlsanity.com/paper/1701.08118/) (2017)
- [ETHOS: an Online Hate Speech Detection Dataset](https://mlsanity.com/paper/2006.08328/) (2020)
- [Spread of hate speech in online social media](https://mlsanity.com/paper/1812.01693/) (2018)
- [Offensive Language Identification in Greek](https://mlsanity.com/paper/2003.07459/) (2020)
- [Offensive Language and Hate Speech Detection for Danish](https://mlsanity.com/paper/1908.04531/) (2019)
- [Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis](https://mlsanity.com/paper/2010.04543/) (2020)
- [Hate Speech detection in the Bengali language: A dataset and its baseline evaluation](https://mlsanity.com/paper/2012.09686/) (2020)
- [Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network](https://mlsanity.com/paper/2004.07807/) (2020)
- [Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi](https://mlsanity.com/paper/2109.03552/) (2021)
- [DeepHateExplainer: Explainable Hate Speech Detection in Under-resourced Bengali Language](https://mlsanity.com/paper/2012.14353/) (2020)
- [Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model](https://mlsanity.com/paper/2111.01515/) (2021)
- [A Large-scale Dataset for Hate Speech Detection on Vietnamese Social Media Texts](https://mlsanity.com/paper/2103.11528/) (2021)
- [Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages](https://mlsanity.com/paper/2204.12543/) (2022)
- [L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models](https://mlsanity.com/paper/2203.13778/) (2022)
- [Hate and Offensive Speech Detection in Hindi and Marathi](https://mlsanity.com/paper/2110.12200/) (2021)
- [Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi](https://mlsanity.com/paper/2204.08669/) (2022)
- [A Dictionary-based Approach to Racism Detection in Dutch Social Media](https://mlsanity.com/paper/1608.08738/) (2016)
- [HateBR: A Large Expert Annotated Corpus of Brazilian Instagram Comments for Offensive Language and Hate Speech Detection](https://mlsanity.com/paper/2103.14972/) (2021)
- [Multimodal Hate Speech Detection from Bengali Memes and Texts](https://mlsanity.com/paper/2204.10196/) (2022)

## Built on by (most cited first, 3 of 3)

- [HateXScore: A Metric Suite for Evaluating Reasoning Quality in Hate Speech Explanations](https://mlsanity.com/paper/2601.13547/) (2026)
- [SEAHateCheck: Functional Tests for Detecting Hate Speech in Low-Resource Languages of Southeast Asia](https://mlsanity.com/paper/2603.16070/) (2026)
- [Boosting Accuracy and Interpretability in Multilingual Hate Speech Detection Through Layer Freezing and Explainable AI](https://mlsanity.com/paper/2601.02697/) (2026)

## Abstract (arXiv)

The expanding influence of social media platforms over the past decade has impacted the way people communicate. The level of obscurity provided by social media and easy accessibility of the internet has facilitated the spread of hate speech. The terms and expressions related to hate speech gets updated with changing times which poses an obstacle to policy-makers and researchers in case of hate speech identification. With growing number of individuals using their native languages to communicate with each other, hate speech in these low-resource languages are also growing. Although, there is awareness about the English-related approaches, much attention have not been provided to these low-resource languages due to lack of datasets and online available data. This article provides a detailed survey of hate speech detection in low-resource languages around the world with details of available datasets, features utilized and techniques used. This survey further discusses the prevailing surveys, overlapping concepts related to hate speech, research challenges and opportunities.