mlsanityData to 7 Oct 2026

One-step and Two-step Classification for Abusive Language Detection on Twitter

arXiv 1706.01206 ↗First posted 5 Jun 2017cs.CLcited by 46

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Abstract (arXiv)

Automatic abusive language detection is a difficult but important task for online social media. Our research explores a two-step approach of performing classification on abusive language and then classifying into specific types and compares it with one-step approach of doing one multi-class classification for detecting sexist and racist languages. With a public English Twitter corpus of 20 thousand tweets in the type of sexism and racism, our approach shows a promising performance of 0.827 F-measure by using HybridCNN in one-step and 0.824 F-measure by using logistic regression in two-steps.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jun 2017.

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Citing papers per year: 2021: 21; 2022: 10; 2023: 7; 2024: 6; 2025: 1; 2026: 1.

46 papers.

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  1. 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Modelscited by 144
  2. 2021Disentangling Hate in Online Memescited by 46
  3. 2021DeepHate: Hate Speech Detection via Multi-Faceted Text Representationscited by 29
  4. 2021A systematic review of Hate Speech automatic detection using Natural Language Processingcited by 26
  5. 2021"Subverting the Jewtocracy": Online Antisemitism Detection Using Multimodal Deep Learningcited by 21
  6. 2021AngryBERT: Joint Learning Target and Emotion for Hate Speech Detectioncited by 19
  7. 2021Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detectioncited by 19
  8. 2022Emotion Based Hate Speech Detection using Multimodal Learningcited by 18
  9. 2022Deep Learning for Hate Speech Detection: A Comparative Studycited by 13
  10. 2023Model-Agnostic Meta-Learning for Multilingual Hate Speech Detectioncited by 11
  11. 2021Interpretable Multi-Modal Hate Speech Detectioncited by 10
  12. 2022Assessing the impact of contextual information in hate speech detectioncited by 10
34 more
  1. 2023Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderatorscited by 10
  2. 2022Predicting Hate Intensity of Twitter Conversation Threadscited by 7
  3. 2022Reliable Decision from Multiple Subtasks through Threshold Optimization: Content Moderation in the Wildcited by 7
  4. 2021NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniquescited by 6
  5. 2021Toxicity Detection can be Sensitive to the Conversational Contextcited by 6
  6. 2024User-Aware Multilingual Abusive Content Detection in Social Mediacited by 6
  7. 2021Sexism detection: The first corpus in Algerian dialect with a code-switching in Arabic/ French and Englishcited by 5
  8. 2021Abusive Language Detection in Heterogeneous Contexts: Dataset Collection and the Role of Supervised Attentioncited by 5
  9. 2023ToxBuster: In-game Chat Toxicity Buster with BERTcited by 5
  10. 2025LLM-C3MOD: A Human-LLM Collaborative System for Cross-Cultural Hate Speech Moderationcited by 5
  11. 2021Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainabilitycited by 4
  12. 2021Cross-lingual hate speech detection based on multilingual domain-specific word embeddingscited by 4
  13. 2023Towards Detecting Contextual Real-Time Toxicity for In-Game Chatcited by 4
  14. 2024Enhancing LLM-based Hatred and Toxicity Detection with Meta-Toxic Knowledge Graphcited by 4
  15. 2021Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Languagecited by 3
  16. 2022Selecting and combining complementary feature representations and classifiers for hate speech detectioncited by 3
  17. 2024An Investigation Into Explainable Audio Hate Speech Detectioncited by 3
  18. 2021IIITG-ADBU@HASOC-Dravidian-CodeMix-FIRE2020: Offensive Content Detection in Code-Mixed Dravidian Textcited by 2
  19. 2021SS-BERT: Mitigating Identity Terms Bias in Toxic Comment Classification by Utilising the Notion of "Subjectivity" and "Identity Terms"cited by 2
  20. 2021Offensive Language Detection with BERT-based models, By Customizing Attention Probabilitiescited by 2
  21. 2024Trustworthy Hate Speech Detection Through Visual Augmentationcited by 2
  22. 2021A study of text representations in Hate Speech Detectioncited by 1
  23. 2021MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detectioncited by 1
  24. 2021Analysing Cyberbullying using Natural Language Processing by Understanding Jargon in Social Mediacited by 1
  25. 2022Going Extreme: Comparative Analysis of Hate Speech in Parler and Gabcited by 1
  26. 2023A Federated Approach for Hate Speech Detectioncited by 1
  27. 2024Deep Prompt Multi-task Network for Abuse Language Detectioncited by 1
  28. 2021Emoji-Based Transfer Learning for Sentiment Taskscited by 0
  29. 2022Detecting Offensive Language on Social Networks: An End-to-end Detection Method based on Graph Attention Networkscited by 0
  30. 2022Multilingual and Multimodal Abuse Detectioncited by 0
  31. 2022Improved two-stage hate speech classification for twitter based on Deep Neural Networkscited by 0
  32. 2023PACO: Provocation Involving Action, Culture, and Oppressioncited by 0
  33. 2024Hate Content Detection via Novel Pre-Processing Sequencing and Ensemble Methodscited by 0
  34. 2026Introducing the Privacy-HSD Trade-off: Hate Speech Detection, but not at the Cost of Privacycited by 0