Hate speech detection using machine learning techniques

Abstract

Social media and sharing platforms are improving in tandem with the internet. Although, humanity has bene ted from these platforms in a variety of ways. However, many people were faced with a variety of obstacles and con icts while using social media. As a result, the usage of derogatory language and hate speech has skyrocketed, posing a major threat. As a result, many varieties of machine language have been developed to overcome this challenge. Hate speech is de ned as the use of slang or insulting phrases directed against a speci c person, race, or any religion. Hate speech and other hate content can be detected using the suggested methodology on platforms like Facebook. Our goal is to develop a model that can identify such actions with more precision so that our current and future generations are not subjected to this scourge.