A Review of Mental Health Analysis Through Social Media Using Machine Learning and Deep Learning Approaches

Artificial intelligence has the potential to transform health care. For that purpose, machine learning (ML) and deep learning (DL) algorithms have been used in the prediction and diagnosis of many diseases. Many people across the world use social media platforms like Twitter, Facebook, Reddit, etc, more often to express their feelings. Mental health has become a big concern after the COVID-19 pandemic and many researchers have applied various ML and DL algorithms to social media data for mental health prediction and analysis. The purpose of this study is to provide a comprehensive analysis of ML and DL algorithms that have been used in the prediction of various mental disorders. This study provides a diverse review of 37 selected research papers. From the selected literature, an accuracy table of ML and DL algorithms for four mental disorders (Depression, Anxiety, Bipolar& ADHA) has been analyzed and created. This study aims to help researchers and practitioners in the future by providing a baseline of the performance of various ML and DL algorithms. Furthermore, we provide a list of publicly available datasets that will act as a knowledge base for future researchers.