mlsanityData to 7 Oct 2026

Contextual-Lexicon Approach for Abusive Language Detection

arXiv 2104.12265 ↗First posted 25 Apr 2021cs.CLcited by 7

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Abstract (arXiv)

Since a lexicon-based approach is more elegant scientifically, explaining the solution components and being easier to generalize to other applications, this paper provides a new approach for offensive language and hate speech detection on social media. Our approach embodies a lexicon of implicit and explicit offensive and swearing expressions annotated with contextual information. Due to the severity of the social media abusive comments in Brazil, and the lack of research in Portuguese, Brazilian Portuguese is the language used to validate the models. Nevertheless, our method may be applied to any other language. The conducted experiments show the effectiveness of the proposed approach, outperforming the current baseline methods for the Portuguese language.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 8 of its 40 references that are in the map. First posted on arXiv 25 Apr 2021.

Builds on

8 of 40 references.

References · 8

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2016Bag of Tricks for Efficient Text Classificationcited by 869
  3. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
  4. 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 268
  5. 2017Detecting Online Hate Speech Using Context Aware Modelscited by 72
  6. 2020Offensive Language Identification in Greekcited by 49
  7. 2018A Unified Deep Learning Architecture for Abuse Detectioncited by 37
  8. 2017Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalizationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 3; 2025: 1; 2026: 2.

7 papers.