Ensemble Hybrid Learning for Depression and Detection

In the digital age, where social media platforms serve as ubiquitous channels for communication and expression, harnessing the power of technology to monitor mental health is both timely and imperative. Our study pioneers a groundbreaking approach to estimate depression intensity by leveraging deep learning techniques on social media data. At its core, our methodology capitalizes on the wealth of information embedded within users' online interactions, offering a novel lens through which to discern subtle indicators of mental health.