Systematic Review on Offensive Language Detection of Multilingual Texts using NLP and Machine Learning Techniques

Roopa G K

Abstract: The widespread usage of social media and online platforms has given rise to a substantial increase in offensive language. Detecting offensive content is crucial to maintaining a healthy online environment and protecting users from harm. Natural Language Processing (NLP) and Machine Learning (ML) techniques have shown promise in addressing this challenge, especially in the context of multilingual texts. This paper presents a systematic review of the existing literature on offensive language detection in multilingual texts, focusing on the NLP and ML methodologies utilized, dataset characteristics, evaluation metrics, and performance comparisons. The review aims to provide an overview of the state-of-the-art techniques, identify key challenges, and suggest future research directions in this area.

Keywords: Natural Language Processing (NLP), Machine Learning (ML), multilingual texts