mlsanityData to 7 Oct 2026

Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms

arXiv 1801.06482 ↗First posted 19 Jan 2018cs.IR cs.CL cs.SIcited by 37

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Abstract (arXiv)

Harassment by cyberbullies is a significant phenomenon on the social media. Existing works for cyberbullying detection have at least one of the following three bottlenecks. First, they target only one particular social media platform (SMP). Second, they address just one topic of cyberbullying. Third, they rely on carefully handcrafted features of the data. We show that deep learning based models can overcome all three bottlenecks. Knowledge learned by these models on one dataset can be transferred to other datasets. We performed extensive experiments using three real-world datasets: Formspring (12k posts), Twitter (16k posts), and Wikipedia(100k posts). Our experiments provide several useful insights about cyberbullying detection. To the best of our knowledge, this is the first work that systematically analyzes cyberbullying detection on various topics across multiple SMPs using deep learning based models and transfer learning.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jan 2018.

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Citing papers per year: 2021: 12; 2022: 14; 2023: 1; 2024: 5; 2025: 4; 2026: 1.

37 papers.

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  1. 2021Towards generalisable hate speech detection: a review on obstacles and solutionscited by 66
  2. 2022Large-Scale Hate Speech Detection with Cross-Domain Transfercited by 39
  3. 2021DeepHate: Hate Speech Detection via Multi-Faceted Text Representationscited by 29
  4. 2022Deep Learning for Hate Speech Detection: A Comparative Studycited by 13
  5. 2022Model Positionality and Computational Reflexivity: Promoting Reflexivity in Data Sciencecited by 13
  6. 2024Meme-ingful Analysis: Enhanced Understanding of Cyberbullying in Memes Through Multimodal Explanationscited by 13
  7. 2022Session-based Cyberbullying Detection in Social Media: A Surveycited by 10
  8. 2022Generalizing Hate Speech Detection Using Multi-Task Learning: A Case Study of Political Public Figurescited by 10
  9. 2022Assessing the impact of contextual information in hate speech detectioncited by 10
  10. 2021An Information Retrieval Approach to Building Datasets for Hate Speech Detectioncited by 9
  11. 2021Uncovering the Limits of Text-based Emotion Detectioncited by 8
  12. 2022On The Robustness of Offensive Language Classifierscited by 8
25 more
  1. 2022Transfer Language Selection for Zero-Shot Cross-Lingual Abusive Language Detectioncited by 8
  2. 2021Evaluation of Deep Learning Models for Hostility Detection in Hindi Textcited by 7
  3. 2024A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMscited by 7
  4. 2021Unsupervised Domain Adaptation for Hate Speech Detection Using a Data Augmentation Approachcited by 6
  5. 2021BERT-Beta: A Proactive Probabilistic Approach to Text Moderationcited by 6
  6. 2021Toxicity Detection can be Sensitive to the Conversational Contextcited by 6
  7. 2022Cyberbullying detection across social media platforms via platform-aware adversarial encodingcited by 6
  8. 2021Cross-lingual hate speech detection based on multilingual domain-specific word embeddingscited by 4
  9. 2022Self-Supervised Pretraining for Differentially Private Learningcited by 4
  10. 2024The Use of a Large Language Model for Cyberbullying Detectioncited by 4
  11. 2021A Neighbourhood Framework for Resource-Lean Content Flaggingcited by 3
  12. 2021Improving Classifier Training Efficiency for Automatic Cyberbullying Detection with Feature Densitycited by 3
  13. 2022Automated Detection of Doxing on Twittercited by 3
  14. 2022Cross-Lingual and Cross-Domain Crisis Classification for Low-Resource Scenarioscited by 3
  15. 2024Explain Thyself Bully: Sentiment Aided Cyberbullying Detection with Explanationcited by 3
  16. 2025Efficient Hate Speech Detection: Evaluating 38 Models from Traditional Methods to Transformerscited by 3
  17. 2022Rethinking and Recomputing the Value of Machine Learning Modelscited by 1
  18. 2024ID-XCB: Data-independent Debiasing for Fair and Accurate Transformer-based Cyberbullying Detectioncited by 1
  19. 2025Detecting harassment and defamation in cyberbullying with emotion-adaptive trainingcited by 1
  20. 2025ExBigBang: A Dynamic Approach for Explainable Persona Classification through Contextualized Hybrid Transformer Analysiscited by 1
  21. 2021Automatic Expansion and Retargeting of Arabic Offensive Language Trainingcited by 0
  22. 2022Improved two-stage hate speech classification for twitter based on Deep Neural Networkscited by 0
  23. 2023Classification of social media Toxic comments using Machine learning modelscited by 0
  24. 2025Detecting cyberbullying in Spanish texts through deep learning techniquescited by 0
  25. 2026Multiclass Hate Speech Detection with RoBERTa-OTA: Integrating Transformer Attention and Graph Convolutional Networkscited by 0