Detection of hate speech
1 article · search the full text for this term
-
Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article