FRAMEWORK FOR PREVENTING CYBERBULLYING IN SOCIAL NETWORKING SITES
Ms.T.Kirubavathi1, Ms.P.Jeevitha2,Ms.S.Jananipriya3,Ms.V.Kavithasri4,
1Assistant Professor, Department of Computer Science & Engineering, Dhirajlal Gandhi College of Technology, Salem, Tamilnadu, India
2,3,4, UG Scholar, Department of Computer Science & Engineering, Dhirajlal Gandhi College of Technology, Salem, Tamilnadu, India
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Abstract - Cyberbullying has emerged as a significant concern in today's digital age, with social networking sites serving as breeding grounds for online harassment and abuse. This study proposes a framework that utilizes a deep learning model to effectively prevent cyberbullying incidents on social networking platforms. The objective is to leverage advanced computational techniques to automatically detect and mitigate instances of cyberbullying, thereby fostering a safer online environment.The framework consists of several key components. Firstly, a comprehensive dataset of cyberbullying instances is curated and annotated to train the deep learning model. The dataset includes textual, visual, and contextual features associated with cyberbullying content, enabling the model to learn the intricate patterns and characteristics indicative of such behavior.Next, a deep learning architecture, such as a convolutional neural network (CNN) or recurrent neural network (RNN), is employed to process the collected data and extract relevant features. The model is trained using both supervised and unsupervised learning techniques to enhance its ability to identify diverse forms of cyberbullying, including text-based harassment, image-based attacks, and subtle contextual cues.The proposed framework's performance is evaluated using various metrics, including precision, recall, and F1-score, through extensive experimentation on a diverse range of cyberbullying scenarios. The results demonstrate the framework's effectiveness in accurately detecting and preventing cyberbullying instances, thereby safeguarding social networking site users from online harassment and abuse.In conclusion, this research presents a robust framework for preventing cyberbullying in social networking sites using a deep learning model. By combining advanced techniques from deep learning, NLP, and computer vision, the framework enables the automated detection and mitigation of cyberbullying incidents, contributing to the creation of a safer and more inclusive online environment.