In this study, we conduct a comparative analysis of the performance of various machine learning and natural language processing models to detect offensive content on social media platforms. In our analysis, language category, social media platform from which they got the dataset, methodology, models used, and finally identified the outperformed model and benefits of the research were tabulated. Finally, the best model was identified among the analyzed models. https://www.propulsiontechjournal.com/index.php/journal/article/view/3505/2400 Share this: Click to print (Opens in new window) Print Click to share on Facebook (Opens in new window) Facebook Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Reddit (Opens in new window) Reddit Click to share on WhatsApp (Opens in new window) WhatsApp Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Like this:Like Loading... Post navigation Enhancing Hate Speech Detection with Large Language Model-Based Dataset Re-Labeling (Openeview) SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (ACL Anthology)