mlsanityData to 7 Oct 2026

Robust Hate Speech Detection in Social Media: A Cross-Dataset Empirical Evaluation

arXiv 2307.01680 ↗First posted 4 Jul 2023cs.CLcited by 28

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Abstract (arXiv)

The automatic detection of hate speech online is an active research area in NLP. Most of the studies to date are based on social media datasets that contribute to the creation of hate speech detection models trained on them. However, data creation processes contain their own biases, and models inherently learn from these dataset-specific biases. In this paper, we perform a large-scale cross-dataset comparison where we fine-tune language models on different hate speech detection datasets. This analysis shows how some datasets are more generalisable than others when used as training data. Crucially, our experiments show how combining hate speech detection datasets can contribute to the development of robust hate speech detection models. This robustness holds even when controlling by data size and compared with the best individual datasets.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 21 of its 52 references that are in the map. First posted on arXiv 4 Jul 2023.

Builds on

21 of 52 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  4. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
  5. 2020HateXplain: A Benchmark Dataset for Explainable Hate Speech Detectioncited by 403
  6. 2018Tune: A Research Platform for Distributed Model Selection and Trainingcited by 395
  7. 2020BERTweet: A pre-trained language model for English Tweetscited by 346
  8. 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 268
  9. 2018Large Scale Crowdsourcing and Characterization of Twitter Abusive Behaviorcited by 265
  10. 2020SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)cited by 138
  11. 2019Multilingual and Multi-Aspect Hate Speech Analysiscited by 133
  12. 2022TimeLMs: Diachronic Language Models from Twittercited by 129
9 more
  1. 2022TweetNLP: Cutting-Edge Natural Language Processing for Social Mediacited by 71
  2. 2020Measuring a hate speech spectrum with faceted Rasch item response theory and perspective-aware, explainable-by-design deep learningcited by 67
  3. 2020"Call me sexist, but...": Revisiting Sexism Detection Using Psychological Scales and Adversarial Samplescited by 48
  4. 2021Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detectioncited by 45
  5. 2020Detecting East Asian Prejudice on Social Mediacited by 40
  6. 2021Overview of the HASOC track at FIRE 2020: Hate Speech and Offensive Content Identification in Indo-European Languagescited by 38
  7. 2022Twitter Topic Classificationcited by 22
  8. 2020Understanding the temporal evolution of COVID-19 research through machine learning and natural language processingcited by 6
  9. 2022Dynamically Refined Regularization for Improving Cross-corpora Hate Speech Detectioncited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 6; 2025: 11; 2026: 6.

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  1. 2024ToxiCraft: A Novel Framework for Synthetic Generation of Harmful Informationcited by 17
  2. 2025HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaignscited by 10
  3. 2023Causality Guided Disentanglement for Cross-Platform Hate Speech Detectioncited by 9
  4. 2023HateModerate: Testing Hate Speech Detectors against Content Moderation Policiescited by 7
  5. 2023Generative AI for Hate Speech Detection: Evaluation and Findingscited by 6
  6. 2024DefVerify: Do Hate Speech Models Reflect Their Dataset's Definition?cited by 6
  7. 2023LLMs and Finetuning: Benchmarking cross-domain performance for hate speech detectioncited by 3
  8. 2024Probing Critical Learning Dynamics of PLMs for Hate Speech Detectioncited by 3
  9. 2025Evaluating Large Language Models for Detecting Antisemitismcited by 3
  10. 2025Toxicity in Online Platforms and AI Systems: A Survey of Needs, Challenges, Mitigations, and Future Directionscited by 3
  11. 2025Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Datacited by 2
  12. 2025Are you sure? Measuring models bias in content moderation through uncertaintycited by 2
16 more
  1. 2025Measuring Online Hate on 4chan using Pre-trained Deep Learning Modelscited by 1
  2. 2025Relation Extraction or Pattern Matching? Unravelling the Generalisation Limits of Language Models for Biographical REcited by 1
  3. 2023DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figurescited by 0
  4. 2024Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Redditcited by 0
  5. 2024The Unappreciated Role of Intent in Algorithmic Moderation of Social Media Contentcited by 0
  6. 2024Hostility Detection in UK Politics: A Dataset on Online Abuse Targeting MPscited by 0
  7. 2025Detoxify: A framework for abusive text transformation using LLMscited by 0
  8. 2025SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Modelscited by 0
  9. 2025Muse-it: A Tool for Analyzing Music Discourse on Redditcited by 0
  10. 2025A Machine Learning Approach for Detection of Mental Health Conditions and Cyberbullying from Social Mediacited by 0
  11. 2026Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasingcited by 0
  12. 2026Do We Still Need Humans in the Loop? Human vs. LLM Annotation in Active Learning for TikTok Hate Speech Detectioncited by 0
  13. 2026A Multi-Dimensional Audit of Politically Aligned Large Language Modelscited by 0
  14. 2026Who Decides What Is Harmful? Content Moderation Policy Through A Multi-Agent Personalised Inference Frameworkcited by 0
  15. 2026From Specialization to Generalization: Instruction-tuned LLMs for Robust Harmful Content Mitigationcited by 0
  16. 2026SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialoguecited by 0