Enhancing Hate Speech Detection on Social Media: A Comparative Analysis of Machine Learning Models and Text Transformation Approaches

Ali Nemati4 days ago29 sec read4 views

The study evaluates machine learning models including BERT and hybrid approaches for detecting hate speech on social media, finding that while advanced models offer superior accuracy, hybrid models excel in specific contexts. Additionally, it introduces text transformation techniques to neutralize harmful content, emphasizing potential future improvements for more effective moderation tools. Content creators should be aware of these advancements to better understand and mitigate the spread of hate speech online.

Read the full article at arXiv cs.CL (NLP)

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