Social media's mental health impact: Behavioral patterns and predictive solutions using machine learning

This study explores the psychological effects of social media by blending survey research with machine learning techniques. We utilize predictive modelling and sentiment analysis to assess how various usage patterns on platforms such as Instagram and Snapchat influence mental health metrics, including anxiety levels, sleep quality, and self-image. Our machine learning framework identifies critical behavioral risk factors, such as late-night usage and compulsive engagement, while natural language processing allows us to delve into the emotional experiences tied to these habits. The research offers practical AI-driven interventions, featuring personalized usage insights and wellness recommendations, showcasing how technology can alleviate digital stress. By merging computational analysis with psychological inquiry, this project delivers valuable findings for users, mental health professionals, and developers aiming to foster healthier online interactions.