mlsanityData to 7 Oct 2026

Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior

arXiv 1802.00393 ↗First posted 1 Feb 2018cs.SIcited by 265

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Abstract (arXiv)

In recent years, offensive, abusive and hateful language, sexism, racism and other types of aggressive and cyberbullying behavior have been manifesting with increased frequency, and in many online social media platforms. In fact, past scientific work focused on studying these forms in popular media, such as Facebook and Twitter. Building on such work, we present an 8-month study of the various forms of abusive behavior on Twitter, in a holistic fashion. Departing from past work, we examine a wide variety of labeling schemes, which cover different forms of abusive behavior, at the same time. We propose an incremental and iterative methodology, that utilizes the power of crowdsourcing to annotate a large scale collection of tweets with a set of abuse-related labels. In fact, by applying our methodology including statistical analysis for label merging or elimination, we identify a reduced but robust set of labels. Finally, we offer a first overview and findings of our collected and annotated dataset of 100 thousand tweets, which we make publicly available for further scientific exploration.

Key facts. Cited by 265 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 53; 2022: 51; 2023: 59; 2024: 57; 2025: 34; 2026: 11.

265 papers.

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  1. 2022ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detectioncited by 419
  2. 2023Toxicity in ChatGPT: Analyzing Persona-assigned Language Modelscited by 356
  3. 2021Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detectioncited by 258
  4. 2021Latent Hatred: A Benchmark for Understanding Implicit Hate Speechcited by 216
  5. 2021On Releasing Annotator-Level Labels and Information in Datasetscited by 123
  6. 2021RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Modelscited by 97
  7. 2021Challenges in Automated Debiasing for Toxic Language Detectioncited by 95
  8. 2022FedPrompt: Communication-Efficient and Privacy Preserving Prompt Tuning in Federated Learningcited by 86
  9. 2021On Measures of Biases and Harms in NLPcited by 81
  10. 2021What's in the Box? A Preliminary Analysis of Undesirable Content in the Common Crawl Corpuscited by 79
  11. 2021Backdoor Pre-trained Models Can Transfer to Allcited by 79
  12. 2021Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreementcited by 71
38 more
  1. 2021Towards generalisable hate speech detection: a review on obstacles and solutionscited by 66
  2. 2022Handling Bias in Toxic Speech Detection: A Surveycited by 60
  3. 2021Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contextscited by 56
  4. 2023ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishingcited by 51
  5. 2021Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-based Hatecited by 50
  6. 2021ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AIcited by 46
  7. 2023Facilitating Fine-grained Detection of Chinese Toxic Language: Hierarchical Taxonomy, Resources, and Benchmarkscited by 45
  8. 2023Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysiscited by 44
  9. 2022Large-Scale Hate Speech Detection with Cross-Domain Transfercited by 39
  10. 2024The Clever Hans Mirage: A Comprehensive Survey on Spurious Correlations in Machine Learningcited by 39
  11. 2022Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarkscited by 36
  12. 2022Toxicity Detection with Generative Prompt-based Inferencecited by 35
  13. 2023COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statementscited by 34
  14. 2021Detecting Harmful Content On Online Platforms: What Platforms Need Vs. Where Research Efforts Gocited by 32
  15. 2024Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Modelscited by 31
  16. 2021Modeling the Second Player in Distributionally Robust Optimizationcited by 29
  17. 2021DeepHate: Hate Speech Detection via Multi-Faceted Text Representationscited by 29
  18. 2023Social Bias Probing: Fairness Benchmarking for Language Modelscited by 29
  19. 2023Robust Hate Speech Detection in Social Media: A Cross-Dataset Empirical Evaluationcited by 28
  20. 2021A systematic review of Hate Speech automatic detection using Natural Language Processingcited by 26
  21. 2021Ruddit: Norms of Offensiveness for English Reddit Commentscited by 26
  22. 2021Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Modelcited by 26
  23. 2023Disentangling Perceptions of Offensiveness: Cultural and Moral Correlatescited by 26
  24. 2024Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Modelscited by 26
  25. 2023Parameter-efficient Modularised Bias Mitigation via AdapterFusioncited by 25
  26. 2024MultiHateClip: A Multilingual Benchmark Dataset for Hateful Video Detection on YouTube and Bilibilicited by 25
  27. 2022Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languagescited by 23
  28. 2024From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasetscited by 23
  29. 2024Hate Personified: Investigating the role of LLMs in content moderationcited by 23
  30. 2022Listening to Affected Communities to Define Extreme Speech: Dataset and Experimentscited by 21
  31. 2024Personas with Attitudes: Controlling LLMs for Diverse Data Annotationcited by 21
  32. 2021AngryBERT: Joint Learning Target and Emotion for Hate Speech Detectioncited by 19
  33. 2021Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detectioncited by 19
  34. 2021Mitigating Racial Biases in Toxic Language Detection with an Equity-Based Ensemble Frameworkcited by 19
  35. 2022Hate Speech and Offensive Language Detection in Bengalicited by 19
  36. 2021Detecting Community Sensitive Norm Violations in Online Conversationscited by 18
  37. 2022Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detectioncited by 18
  38. 2022Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworkscited by 18

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