Identifying Mental Health Indicators from Social Media Activity Using AI

Mental health challenges among youth have become a pressing issue, with rising rates of stress, anxiety, and depression highlighting the need for early detection and support systems.The purpose of this study is to explore the use of AI in identifying mental health signals among youth based on data collected from social media posts.Accordingly, a mental health dataset from Kaggle is used to train a Nave Bayes classifier that categorizes social media posts into various mental health conditions.The results showed that the Nave Bayes classifier was able to predict various mental health conditions with an accuracy of 64%, which is an encouraging baseline.