mlsanityData to 7 Oct 2026

ETHOS: an Online Hate Speech Detection Dataset

arXiv 2006.08328 ↗First posted 11 Jun 2020cs.CL cs.LG stat.MLcited by 66

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Abstract (arXiv)

Online hate speech is a recent problem in our society that is rising at a steady pace by leveraging the vulnerabilities of the corresponding regimes that characterise most social media platforms. This phenomenon is primarily fostered by offensive comments, either during user interaction or in the form of a posted multimedia context. Nowadays, giant corporations own platforms where millions of users log in every day, and protection from exposure to similar phenomena appears to be necessary in order to comply with the corresponding legislation and maintain a high level of service quality. A robust and reliable system for detecting and preventing the uploading of relevant content will have a significant impact on our digitally interconnected society. Several aspects of our daily lives are undeniably linked to our social profiles, making us vulnerable to abusive behaviours. As a result, the lack of accurate hate speech detection mechanisms would severely degrade the overall user experience, although its erroneous operation would pose many ethical concerns. In this paper, we present 'ETHOS', a textual dataset with two variants: binary and multi-label, based on YouTube and Reddit comments validated using the Figure-Eight crowdsourcing platform. Furthermore, we present the annotation protocol used to create this dataset: an active sampling procedure for balancing our data in relation to the various aspects defined. Our key assumption is that, even gaining a small amount of labelled data from such a time-consuming process, we can guarantee hate speech occurrences in the examined material.

Key facts. Cited by 66 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jun 2020.

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Citing papers per year: 2022: 9; 2023: 8; 2024: 19; 2025: 21; 2026: 9.

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  2. 2026On-Policy Context Distillation for Language Modelscited by 161
  3. 2022Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrationscited by 116
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  6. 2023Active Learning Principles for In-Context Learning with Large Language Modelscited by 53
  7. 2024From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasetscited by 23
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  10. 2025System Prompt Optimization with Meta-Learningcited by 18
  11. 2024Task Facet Learning: A Structured Approach to Prompt Optimizationcited by 17
  12. 2022KOLD: Korean Offensive Language Datasetcited by 14
38 more
  1. 2024Misconfidence-based Demonstration Selection for LLM In-Context Learningcited by 14
  2. 2024MetaHate: A Dataset for Unifying Efforts on Hate Speech Detectioncited by 14
  3. 2022Deep Learning for Hate Speech Detection: A Comparative Studycited by 13
  4. 2024Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Datasetcited by 13
  5. 2024BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Banglacited by 10
  6. 2025GAAPO: Genetic Algorithmic Applied to Prompt Optimizationcited by 10
  7. 2024Introducing MAPO: Momentum-Aided Gradient Descent Prompt Optimizationcited by 8
  8. 2022"It's Not Just Hate'': A Multi-Dimensional Perspective on Detecting Harmful Speech Onlinecited by 7
  9. 2023Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptionscited by 7
  10. 2022An Attention Matrix for Every Decision: Faithfulness-based Arbitration Among Multiple Attention-Based Interpretations of Transformers in Text Classificationcited by 6
  11. 2024Investigating Annotator Bias in Large Language Models for Hate Speech Detectioncited by 6
  12. 2024Beyond Labels: Aligning Large Language Models with Human-like Reasoningcited by 6
  13. 2025MAPGD: Multi-Agent Prompt Gradient Descent for Collaborative Prompt Optimizationcited by 6
  14. 2022CoRAL: a Context-aware Croatian Abusive Language Datasetcited by 4
  15. 2024Zero-to-Strong Generalization: Eliciting Strong Capabilities of Large Language Models Iteratively without Gold Labelscited by 4
  16. 2022Hypothesis Engineering for Zero-Shot Hate Speech Detectioncited by 3
  17. 2023Identity Construction in a Misogynist Incels Forumcited by 3
  18. 2024Quantifying Stereotypes in Languagecited by 3
  19. 2024Dynamic Uncertainty Ranking: Enhancing Retrieval-Augmented In-Context Learning for Long-Tail Knowledge in LLMscited by 3
  20. 2025A Checks-and-Balances Framework for Context-Aware Ethical AI Alignmentcited by 3
  21. 2025Context Engineering for Trustworthiness: Rescorla Wagner Steering Under Mixed and Inappropriate Contextscited by 3
  22. 2025Prompts Generalize with Low Data: Non-vacuous Generalization Bounds for Optimizing Prompts with More Informative Priorscited by 3
  23. 2025CoPE: A Small Language Model for Steerable and Scalable Content Labelingcited by 3
  24. 2026When Context Returns: Toward Robust Internalization in On-Policy Distillationcited by 3
  25. 2024Effective In-Context Example Selection through Data Compressioncited by 2
  26. 2024MHS-STMA: Multimodal Hate Speech Detection via Scalable Transformer-Based Multilevel Attention Frameworkcited by 2
  27. 2024A Survey on Automatic Online Hate Speech Detection in Low-Resource Languagescited by 2
  28. 2025A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in Englishcited by 2
  29. 2025LLM Based Bayesian Optimization for Prompt Searchcited by 2
  30. 2025OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Modelscited by 2
  31. 2022Truthful Meta-Explanations for Local Interpretability of Machine Learning Modelscited by 1
  32. 2023On Bias and Fairness in NLP: Investigating the Impact of Bias and Debiasing in Language Models on the Fairness of Toxicity Detectioncited by 1
  33. 2025ChildGuard: A Specialized Dataset for Combatting Child-Targeted Hate Speechcited by 1
  34. 2025Grammar-Guided Evolutionary Search for Discrete Prompt Optimisationcited by 1
  35. 2025GreenTEA: Gradient Descent with Topic-modeling and Evolutionary Auto-promptingcited by 1
  36. 2025UniAPO: Unified Multimodal Automated Prompt Optimizationcited by 1
  37. 2025Semantic Anchors in In-Context Learning: Why Small LLMs Cannot Flip Their Labelscited by 1
  38. 2026Bye Bye Perspective API: Lessons for Building and Governing Measurement Infrastructurecited by 1

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