mlsanityData to 7 Oct 2026

BRUMS at SemEval-2020 Task 12 : Transformer based Multilingual Offensive Language Identification in Social Media

arXiv 2010.06278 ↗First posted 13 Oct 2020cs.CL cs.AIcited by 10

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Abstract (arXiv)

In this paper, we describe the team textitBRUMS entry to OffensEval 2: Multilingual Offensive Language Identification in Social Media in SemEval-2020. The OffensEval organizers provided participants with annotated datasets containing posts from social media in Arabic, Danish, English, Greek and Turkish. We present a multilingual deep learning model to identify offensive language in social media. Overall, the approach achieves acceptable evaluation scores, while maintaining flexibility between languages.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Oct 2020.

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Citing papers per year: 2021: 8; 2022: 2.

10 papers.

  1. 2021MUDES: Multilingual Detection of Offensive Spanscited by 30
  2. 2021Multilingual Offensive Language Identification for Low-resource Languagescited by 22
  3. 2021Comparing Approaches to Dravidian Language Identificationcited by 11
  4. 2021WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spanscited by 6
  5. 2022Predicting the Type and Target of Offensive Social Media Posts in Marathicited by 5
  6. 2021Transformers to Fight the COVID-19 Infodemiccited by 4
  7. 2021Language Identification of Hindi-English tweets using code-mixed BERTcited by 4
  8. 2022DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domaincited by 4
  9. 2021TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguationcited by 3
  10. 2021Offensive Language Detection with BERT-based models, By Customizing Attention Probabilitiescited by 2