mlsanityData to 7 Oct 2026

Offensive Language Identification in Transliterated and Code-Mixed Bangla

arXiv 2311.15023 ↗First posted 25 Nov 2023cs.CLcited by 12

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Abstract (arXiv)

Identifying offensive content in social media is vital for creating safe online communities. Several recent studies have addressed this problem by creating datasets for various languages. In this paper, we explore offensive language identification in texts with transliterations and code-mixing, linguistic phenomena common in multilingual societies, and a known challenge for NLP systems. We introduce TB-OLID, a transliterated Bangla offensive language dataset containing 5,000 manually annotated comments. We train and fine-tune machine learning models on TB-OLID, and we evaluate their results on this dataset. Our results show that English pre-trained transformer-based models, such as fBERT and HateBERT achieve the best performance on this dataset.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 13 of its 26 references that are in the map. First posted on arXiv 25 Nov 2023.

Builds on

13 of 26 references.

References · 13

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  4. 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 268
  5. 2019SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)cited by 206
  6. 2020HateBERT: Retraining BERT for Abusive Language Detection in Englishcited by 206
  7. 2020Offensive Language Identification in Greekcited by 49
  8. 2019Offensive Language and Hate Speech Detection for Danishcited by 48
  9. 2020Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Networkcited by 30
  10. 2021FBERT: A Neural Transformer for Identifying Offensive Contentcited by 30
  11. 2021Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathicited by 28
  12. 2020DeepHateExplainer: Explainable Hate Speech Detection in Under-resourced Bengali Languagecited by 26
1 more
  1. 2022Predicting the Type and Target of Offensive Social Media Posts in Marathicited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 6; 2026: 1.

12 papers.

  1. 2024BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Banglacited by 10
  2. 2025CodeMixBench: Evaluating Code-Mixing Capabilities of LLMs Across 18 Languagescited by 8
  3. 2025LLM-Based Multi-Task Bangla Hate Speech Detection: Type, Severity, and Targetcited by 6
  4. 2024A Federated Learning Approach to Privacy Preserving Offensive Language Identificationcited by 4
  5. 2025Beyond Monolingual Assumptions: A Survey of Code-Switched NLP in the Era of Large Language Models across Modalitiescited by 4
  6. 2024CSEPrompts: A Benchmark of Introductory Computer Science Promptscited by 3
  7. 2024MasonPerplexity at Multimodal Hate Speech Event Detection 2024: Hate Speech and Target Detection Using Transformer Ensemblescited by 2
  8. 2024EmoMix-3L: A Code-Mixed Dataset for Bangla-English-Hindi Emotion Detectioncited by 2
  9. 2025UNITYAI-GUARD: Pioneering Toxicity Detection Across Low-Resource Indian Languagescited by 2
  10. 2025Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?cited by 2
  11. 2025Web(er) of Hate: A Survey on How Hate Speech Is Typedcited by 0
  12. 2026Can LLMs Follow the Pulse of a Crisis? Evaluating Crisis Sentiment in Bangladesh's July Uprisingcited by 0