Predicting Mental Disorders with Nonlinear Variational Inequalities: Insights from Diverse Online Social Network Datasets

Introduction: Online social networks provide a wealth of data for predicting mental disorders through the analysis of user-generated content, network connections, and behavioural patterns. This research explores deep learning and machine learning techniques to develop accurate and scalable predictive models, offering promising opportunities for early detection, intervention, and personalized support in mental health care. By reviewing current research, challenges, and various deep learning architectures, the paper highlights the advancements and future directions in utilizing these techniques for mental disorder prediction.