• Bhavesh Chandrakant Borole
• Rushikesh Sunil Shrikhande
• Divya Ninaji Choudhari
• Vaishnavi Pradip Patil
• Madhuri. R. Rajput

Hate speech is any expression that targets an individual or group of people because of their colour, national origin, religion, sexual orientation, or other characteristics. Though there are several ways to convey it, including online Both online and off, social media's growing popularity has greatly expanded its use and severity. Thus, finding and analyzing the unstructured data of particular social media posts with the intention of spreading hate in the comment sections is the goal of this study. We suggest FADOHS, a unique framework that combines data analysis and natural language processing techniques, as a solution to this problem. Its goal is to make all social media providers aware of how common hate speech is on the platform. In particular, we examine recent postings and comments on these pages using sentiment and emotion analysis algorithms. Posts that may contain terms that dehumanise people will be examined before being sent to the clustering algorithm for additional analysis. The experimental results show that the suggested FADOHS framework can achieve roughly 10% better precision, recall, and F1 scores than the state-of-the-art method.

Emotion recognition, clustering algorithm, sentiment analysis, data mining.

"Integration of Unstructured Data of Hate Speech on Facebook Using Sentiment and Emotion", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d17-d20, April-2024, Available :http://www.jetir.org/papers/JETIR2404304.pdf

"Integration of Unstructured Data of Hate Speech on Facebook Using Sentiment and Emotion", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd17-d20, April-2024, Available at : http://www.jetir.org/papers/JETIR2404304.pdf