Hate Speech Detection Using Deep Learning

Abstract

Abstract: Hate speech is a form of verbal abuse that targetsindividuals depending on their race, religion, ethnicity, gender, sexual orientation, or other personal characteristics. It can be spoken, written, or displayed, and can be found in a variety of contexts, including online, in person, and in the media. Hate Speech has the potential to have a devastating impact on victims, causing emotional distress, social isolation, and even physical harm. Recognizing hate speech is a challenging task, especially in multilingual contexts. This is because hate speech can be expressed in many ways, and can be difficult todistinguish from other forms of speech. However, Artificial Intelligence (AI) has advanced recently, and have made it possible to develop effective hate speech detection systems. Hate speech detection is a challenging task, especially in multilingual contexts. This survey paper reviews the recent advances in hate speech detection using BERT and CNN models. We explored the various approaches that have been proposed, the challengesfaced, and the paths that research will take in the future