“This paper aims to provide systematic bibliometric analysis and mappings of existing literature for Hate Speech Detection and to identify the existence of Hate speech-related research. Bibliometric Analysis of Machine Learning and Deep Learning articles in Hate, hostile, and abusive speech is considered. This is accomplished using the SCOPUS database, with tools like VOSViewer, Biblioshiny, and ScienceScape. Explored parameters consist of the document type, most active countries, top journals, relevant affiliations, trending topics, etc. It is observed that the current literature on hate speech is concentrated on a specific philosophy. An unexpected need to rectify this situation was evident from this bibliometric analysis due to recent occurrences of hate speech in the digital world.”https://jscires.org/article/488Share this:FacebookXLike this:Like Loading... Post navigation Detecting Bots to Distinguish Hate Speech on Social Media (IEEE) What is so special about online (as compared to offline) hate speech? (Ethnicities)