A Machine Learning Classification Model for Predicting Depression Using Social Media Posts of User

Depression is a prevalent mental health disorder, with social media platforms serving as a rich source of data for identifying and understanding depressive symptoms. This paper presents a machine learning stratification model designed to predict depression using social media data collected from Twitter, Facebook, and Reddit. The model incorporates sentiment analysis, keyword labeling, and stratification techniques to accurately categorize depressive posts. The research evaluates the model's performance using various metrics and compares it against traditional methods for identifying depressive content.