Early Prediction of Depression on Social Networks using BERT Model

This research aims to build an advanced system that leverages deep learning to predict signs of depression based on social media posts. By utilizing BERT, a powerful neural network model, our system can identify subtle indicators of depression in online content. This method seeks to significantly enhance the accuracy of mental health assessments, providing timely and effective support to those who may be at risk. Our work aspires to contribute to the field of mental health technology, offering essential tools for clinicians, researchers, and mental health professionals. By applying the latest deep learning techniques, we aim to bridge the gap between technology and mental health, creating new ways to detect and address mental health issues early.