AI-Powered Mental Health Insights: A Comprehensive Review of Machine Learning & Deep Learning Approaches for Social Media Analysis
Authors:-Mrs.R.Veera Meenakshi, B.Vanitha Sri, V.N.V.Karthikeya, P.G.Pranava, K.Uday Meher, A.Sreeja
Abstract-Artificial intelligence is revolutionizing healthcare, particularly in the prediction and diagnosis of various diseases through machine learning (ML) and deep learning (DL) algorithms. With the widespread use of social media platforms like Twitter, Facebook, and Reddit, individuals frequently express their thoughts and emotions online. Mental health has emerged as a significant concern, especially following the COVID-19 pandemic, prompting researchers to leverage ML and DL techniques to analyse social media data for mental health prediction. This study offers a comprehensive review of ML and DL algorithms applied to the prediction of mental disorders, based on an analysis of 37 selected research papers. It presents a comparative accuracy table of ML and DL models for four key mental disorders: Depression, Anxiety, Bipolar Disorder, and ADHD. The findings aim to provide a foundational reference for researchers and practitioners, assisting in future advancements in this field. Additionally, this study compiles a list of publicly available datasets, serving as a valuable resource for further research in mental health analysis using artificial intelligence.
