Breaking Barriers: An Innovative Algorithm to Stop Cyberbullying on Personal Blogs

The growing threat of cyberbullying appears as a serious and urgent worry in the modern digital landscape, where the internet serves as a canvas for personal expression through blogs and personal webpages. It is of the utmost significance to protect the valued freedom of internet artists and to uphold the purity of individual voices. We present a ground-breaking algorithm that was painstakingly designed to identify and stop cyberbullying in the context of personal blogs and webpages in response to this challenging challenge. Convolutional Neural Networks (CNNs), BERT (Bidirectional Encoder Representations from Transformers), and stemming approaches are all seamlessly combined in our ground-breaking strategy to create a robust defence against online abuse. Using CNNs’ strong capabilities, it enables the detection of regional textual patterns and traits that could be used as red flags for cyberbullying. BERT goes deeply into the intricate tapestry of words, phrases, and sentences to ensure that the genuine intentions underlying the text are made clear thanks to its exceptional ability in contextual language interpretation. stemming procedure makes the detection system more precise and effective by assisting in the identification of dangerous words.