• Aman Singh
• ANURAG TIWARI
• NITIN KUMAR SHUKLA

The exponential growth of digital communication platforms such as social media networks, online forums, and instant messaging applications has led to a parallel increase in cyberbullying incidents. Cyberbullying refers to the intentional use of digital media to harass, threaten, abuse, or humiliate individuals through offensive textual content. Such behavior has serious psychological, emotional, and social consequences, including anxiety, depression, social isolation, and, in extreme cases, self-harm. Manual moderation of online content is increasingly impractical due to the massive volume of user-generated data produced every day. To address this challenge, this research proposes a Desktop-Based Cyberbullying Detection System that employs Machine Learning (ML) and Natural Language Processing (NLP) techniques to automatically detect and classify cyberbullying content.

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"Desktop-Based Cyberbullying Detection System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.d74-d79, January-2026, Available :http://www.jetir.org/papers/JETIR2601310.pdf

"Desktop-Based Cyberbullying Detection System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. ppd74-d79, January-2026, Available at : http://www.jetir.org/papers/JETIR2601310.pdf