MindScope: A Comprehensive Review of Mental Health Assessment via Social Media Using Machine Learning and Deep Learning

Abstract-Artificial intelligence holds significant potential to revolutionize healthcare. Machine learning (ML) and deep learning (DL) techniques have been increasingly utilized for predicting and diagnosing a wide range of diseases. In addition, social media platforms such as Twitter, Facebook, and Reddit have become popular outlets for individuals to share their emotions and experiences. Following the COVID-19 pandemic, mental health concerns have escalated, prompting numerous studies that apply ML and DL models to analyses social media data for predicting mental health issues. This research aims to offer an in-depth review of the ML and DL algorithms applied to the prediction of various mental health disorders. It presents an extensive overview of 37 research papers, analysing and compiling a table of the accuracy of these algorithms across four key mental health conditions: Depression, Anxiety, Bipolar Disorder, and ADHD. The study is intended to serve as a foundational resource for future researchers and practitioners, offering insights into the performance of different ML and DL approaches. Additionally, it includes a compilation of publicly available datasets, providing valuable resources for ongoing research in this area.