• Penmetsa Gopala Krishnam Raju
• Adabala Divya Sai Suseela
• Lankey Laxmi Sri Suraj
• Karra Santhosh Kumar
• Chalamcharla Baswanth Kusumakar

The exponential growth of digital platforms has created opportunities for global communication but also fostered the proliferation of cyber-hate speech. Effective detection mechanisms are essential, as online hate speech contributes to real-world violence, discrimination, and psychological harm. This study proposes a multi-stage approach combining machine learning and fuzzy logic to detect and mitigate cyber-hate speech effectively. Leveraging diverse datasets, advanced algorithms, and linguistic analysis, the system addresses limitations in existing solutions. Expected outcomes include higher accuracy in detecting hate speech, efficient handling of ambiguous content, and fostering safer online environments.

Cyber-Hate Detection, Machine Learning, Fuzzy Logic, Social Media, Hate Speech, Deep Learning, Contextual Analysis, Real-Time Processing, Scalability, Multilingual Datasets.

"Intelligent Detection of Cyber hate: Integrating Machine Learning with Fuzzy Logic", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.e494-e499, March-2025, Available :http://www.jetir.org/papers/JETIR2503470.pdf

"Intelligent Detection of Cyber hate: Integrating Machine Learning with Fuzzy Logic", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppe494-e499, March-2025, Available at : http://www.jetir.org/papers/JETIR2503470.pdf