Mental Health Monitoring in the Digital Age

Abstract

Social media has become a significant factor in the development of mental diseases, with the potential to significantly impact people's lives. This study explores the use of computational approaches and deep learning models to identify linguistic indicators suggestive of mental diseases such as depression, anorexia, and self-harm. The study also highlights the complex relationship between emotions and the underlying causes of mental diseases, emphasizing the need for understanding emotional triggers. The research demonstrates the effectiveness of machine learning models in detecting anxiety and depression on websites like Twitter, Facebook, and Reddit, particularly during the COVID-19 pandemic. The study highlights the potential of data mining techniques for automating the diagnosis of Social Network Mental Disorders among social media users, aiming to improve lives and address the rising incidence of mental illnesses in society.