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An AI-Based Analysis of Music for Improving Mental Health in Adolescence

CSEF · 2026 Behavioral & Social Sciences (Senior Division)

Amy Zhang

Overview

As stress levels of adolescents grow in modern society, the risk of severe mental disorders has increased. Recent studies reveal the potential of music to alleviate negative emotions. This study addresses the underrepresentation of adolescents in this field and helps boost adolescent mental health through music. A survey was conducted among adolescents on their selection of songs in different emotion states. 57 valid responses with 15 selected songs were analyzed for patterns in music selection and the associated emotion states. Two AI-based tools were applied to the selected songs for predicting their conveyed moods. The mood predictions were compared against the emotion states associated with music selection from the survey. The analysis results show 47% and 39% survey participants would listen to music when feeling stressed and sad, respectively, confirming that music is a viable coping method for adolescents experiencing negative emotions. The observed trends between adolescent music selection and their emotion states suggest the potential to build a model that can predict adolescent music selection under different emotion states.

Competition history

  • CSEF 2026 Behavioral & Social Sciences (Senior Division) · Entry S-03-32

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