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Found 7 papers, 0 papers with code
Finnish Hate-Speech Detection on Social Media Using CNN and FinBERT
The majority of this research has concentrated on English, although one notices the emergence of multilingual detection tools such as multilingual-BERT (mBERT).
Data Expansion Using WordNet-based Semantic Expansion and Word Disambiguation for Cyberbullying Detection
Automatic identification of cyberbullying from textual content is known to be a challenging task.
BanglaHateBERT: BERT for Abusive Language Detection in Bengali
This paper introduces BanglaHateBERT, a retrained BERT model for abusive language detection in Bengali.
A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMs
The surge of interest in data augmentation within the realm of NLP has been driven by the need to address challenges posed by hate speech domains, the dynamic nature of social media vocabulary, and the demands for large-scale neural networks requiring extensive training data.
Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection
With proliferation of user generated contents in social media platforms, establishing mechanisms to automatically identify toxic and abusive content becomes a prime concern for regulators, researchers, and society.
A systematic review of Hate Speech automatic detection using Natural Language Processing
With the multiplication of social media platforms, which offer anonymity, easy access and online community formation, and online debate, the issue of hate speech detection and tracking becomes a growing challenge to society, individual, policy-makers and researchers.
Team Oulu at SemEval-2020 Task 12: Multilingual Identification of Offensive Language, Type and Target of Twitter Post Using Translated Datasets
We handled offensive language in five languages: English, Greek, Danish, Arabic, and Turkish.
