A Study on Foul Language Detection

Abstract

There is always a substantial risk of scorn and even harassment when one engages in online activity, whether on message board discussions, comments, or social media. Words that are inappropriate are unfortunately frequent online and can have a significant impact on a community's civility or a user's experience. To fight abusive language, many websites have standards and guidelines that users must follow, as well as human editors who work in tandem with systems that utilize regular expressions and blacklists to capture foul language and so remove a post. The demand for high-quality automatic abusive language classifiers is growing as individuals speak more online. As this is the complex problem ML is being suggested as an effective tool to detect Abuse language. Here is the detailed analysis of the existing systems comparing their methodology and accuracy.