• Nellore.Vinay
• Sheela Santha Kumari
• Ponmali.S
• Prasanna.S

People now utilize the internet as a major medium to voice their opinions. Blogging and social networking websites allow users to post whatever they desire. There are times, though, when specially designed content for a group of individuals to create hatred or discrimination is brought to the forefront, leading to issues in society. This kind of content is known as hate speech. Hate speech can diminish social peace and harmony to a large extent. On some occasions, it has led to extremism and social conflict. Explained are the various types of hate speech—e.g., racism, sexism, religious hate speech, etc.—and the ways used to fight them. We also define the problem and the solution for hate speech detection on the public internet. Consequently, internet hate speech needs to be tracked. In this case, we review related work in the hate speech detection field. In addition to identifying hate speech on the internet, our suggested methodology classifies it as "hate speech," "offensive speech," "fair speech," etc. As data collected is processed, hate speech reports could be created, making internet usage more accessible to users of all types.

Hate Speech, Social media platforms, Discrimination, Extremism, Racism, Sexism, Religion.

"MACHINE LEARNING MODEL FOR HATE SPEECH DETECTION IN ONLINE CONTENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.e339-e346, April-2025, Available :http://www.jetir.org/papers/JETIR2504443.pdf

"MACHINE LEARNING MODEL FOR HATE SPEECH DETECTION IN ONLINE CONTENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppe339-e346, April-2025, Available at : http://www.jetir.org/papers/JETIR2504443.pdf