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Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech

arXiv 2107.08720 ↗First posted 19 Jul 2021cs.CL cs.CYcited by 81

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Abstract (arXiv)

Undermining the impact of hateful content with informed and non-aggressive responses, called counter narratives, has emerged as a possible solution for having healthier online communities. Thus, some NLP studies have started addressing the task of counter narrative generation. Although such studies have made an effort to build hate speech / counter narrative (HS/CN) datasets for neural generation, they fall short in reaching either high-quality and/or high-quantity. In this paper, we propose a novel human-in-the-loop data collection methodology in which a generative language model is refined iteratively by using its own data from the previous loops to generate new training samples that experts review and/or post-edit. Our experiments comprised several loops including dynamic variations. Results show that the methodology is scalable and facilitates diverse, novel, and cost-effective data collection. To our knowledge, the resulting dataset is the only expert-based multi-target HS/CN dataset available to the community.

Key facts. Cited by 81 papers in the map (data through 7 Oct 2026). Builds on 20 of its 40 references that are in the map. First posted on arXiv 19 Jul 2021.

Builds on

20 of 40 references.

References · 20

  1. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  2. 2019Defending Against Neural Fake Newscited by 553
  3. 2019Release Strategies and the Social Impacts of Language Modelscited by 505
  4. 2020HateXplain: A Benchmark Dataset for Explainable Hate Speech Detectioncited by 403
  5. 2019Social Bias Frames: Reasoning about Social and Power Implications of Languagecited by 377
  6. 2020Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detectioncited by 217
  7. 2018Hate Speech Dataset from a White Supremacy Forumcited by 196
  8. 2019Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attackcited by 176
  9. 2020Directions in Abusive Language Training Data: Garbage In, Garbage Outcited by 139
  10. 2019A Benchmark Dataset for Learning to Intervene in Online Hate Speechcited by 128
  11. 2019CONAN -- COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speechcited by 109
  12. 2017Measuring the Reliability of Hate Speech Annotations: The Case of the European Refugee Crisiscited by 95
8 more
  1. 2018Thou shalt not hate: Countering Online Hate Speechcited by 64
  2. 2020Generating Counter Narratives against Online Hate Speech: Data and Strategiescited by 58
  3. 2020Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspectivecited by 43
  4. 2018Augmenting Neural Response Generation with Context-Aware Topical Attentioncited by 27
  5. 2018Analyzing the hate and counter speech accounts on Twittercited by 21
  6. 2020The Role of Pragmatic and Discourse Context in Determining Argument Impactcited by 18
  7. 2019Determining Relative Argument Specificity and Stance for Complex Argumentative Structurescited by 7
  8. 2020Toward Stance-based Personas for Opinionated Dialoguescited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 9; 2023: 15; 2024: 25; 2025: 15; 2026: 14.

81 papers.

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  1. 2023Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructionscited by 377
  2. 2022Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Counteringcited by 40
  3. 2022Hate Speech and Counter Speech Detection: Conversational Context Does Mattercited by 32
  4. 2022Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Studycited by 30
  5. 2022CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeechcited by 28
  6. 2024Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Modelscited by 26
  7. 2023Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Languagecited by 22
  8. 2024NLP for Counterspeech against Hate: A Survey and How-To Guidecited by 21
  9. 2024NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helpscited by 19
  10. 2021SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasetscited by 18
  11. 2022Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitionscited by 18
  12. 2023Understanding Counterspeech for Online Harm Mitigationcited by 17
38 more
  1. 2024On Zero-Shot Counterspeech Generation by LLMscited by 17
  2. 2023Targeted Data Generation: Finding and Fixing Model Weaknessescited by 15
  3. 2024Contextualized Counterspeech: Strategies for Adaptation, Personalization, and Evaluationcited by 15
  4. 2023DisCGen: A Framework for Discourse-Informed Counterspeech Generationcited by 14
  5. 2023Counterspeeches up my sleeve! Intent Distribution Learning and Persistent Fusion for Intent-Conditioned Counterspeech Generationcited by 13
  6. 2022Detecting Unintended Social Bias in Toxic Language Datasetscited by 12
  7. 2023D-CALM: A Dynamic Clustering-based Active Learning Approach for Mitigating Biascited by 12
  8. 2024Outcome-Constrained Large Language Models for Countering Hate Speechcited by 12
  9. 2024Is Safer Better? The Impact of Guardrails on the Argumentative Strength of LLMs in Hate Speech Counteringcited by 11
  10. 2021Multilingual Counter Narrative Type Classificationcited by 9
  11. 2023Countering Misinformation via Emotional Response Generationcited by 9
  12. 2024Subjective textitIsms? On the Danger of Conflating Hate and Offence in Abusive Language Detectioncited by 9
  13. 2021Revisiting Contextual Toxicity Detection in Conversationscited by 8
  14. 2024POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference Optimizationcited by 8
  15. 2022Perspectives on Incorporating Expert Feedback into Model Updatescited by 7
  16. 2023HateModerate: Testing Hate Speech Detectors against Content Moderation Policiescited by 7
  17. 2023Weigh Your Own Words: Improving Hate Speech Counter Narrative Generation via Attention Regularizationcited by 7
  18. 2024Basque and Spanish Counter Narrative Generation: Data Creation and Evaluationcited by 7
  19. 2024A Multi-Aspect Framework for Counter Narrative Evaluation using Large Language Modelscited by 6
  20. 2024A LLM-Based Ranking Method for the Evaluation of Automatic Counter-Narrative Generationcited by 6
  21. 2024Decoding Hate: Exploring Language Models' Reactions to Hate Speechcited by 6
  22. 2023On the rise of fear speech in online social mediacited by 5
  23. 2024Low-Resource Counterspeech Generation for Indic Languages: The Case of Bengali and Hindicited by 5
  24. 2024CrowdCounter: A benchmark type-specific multi-target counterspeech datasetcited by 5
  25. 2024Assessing the Human Likeness of AI-Generated Counterspeechcited by 5
  26. 2024An Active Learning Framework for Inclusive Generation by Large Language Modelscited by 5
  27. 2025How to Enable Effective Cooperation Between Humans and NLP Models: A Survey of Principles, Formalizations, and Beyondcited by 4
  28. 2025CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMscited by 4
  29. 2022Human-in-the-Loop Hate Speech Classification in a Multilingual Contextcited by 3
  30. 2024Fine-tuning with HED-IT: The impact of human post-editing for dialogical language modelscited by 3
  31. 2024SubData: Bridging Heterogeneous Datasets to Enable Theory-Driven Evaluation of Political and Demographic Perspectives in LLMscited by 3
  32. 2025Toxicity in Online Platforms and AI Systems: A Survey of Needs, Challenges, Mitigations, and Future Directionscited by 3
  33. 2025Breaking the Safety-Capability Tradeoff: Reinforcement Learning with Verifiable Rewards Maintains Safety Guardrails in LLMscited by 3
  34. 2022SOLD: Sinhala Offensive Language Datasetcited by 2
  35. 2023LAHM : Large Annotated Dataset for Multi-Domain and Multilingual Hate Speech Identificationcited by 2
  36. 2023Towards a Unified Framework for Adaptable Problematic Content Detection via Continual Learningcited by 2
  37. 2024Consolidating Strategies for Countering Hate Speech Using Persuasive Dialoguescited by 2
  38. 2024Hatred Stems from Ignorance! Distillation of the Persuasion Modes in Countering Conversational Hate Speechcited by 2

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