Research Projects

The study aims to predict the risk of depression based on an individual's online music listening habits. The research will use big data to identify long-term traits related to one's tendencies to persist in depression states and explore cross-cultural differences in music consumption. The study will use data from Last.fm, a music streaming platform in India, and collaborate with top platforms like Wynk music, JioSaavn, Spotify India, and Amazon music. The objective is to identify music choices and listening patterns associated with individuals with high risk of depression and other potential mental health problems, as well as examine key musical and individual factors that regulate this. The research will allow for a predictive model to detect the risk of depression relying on digital music traces, allowing for timely intervention. The study will also identify gender-specific, trait-specific music listening patterns that moderate depression and suicide risk. The research will involve a cross-disciplinary approach, utilizing naturalistic contexts and data analytics to create a valuable database for further research. The project aims to empower individuals by making them aware of their music consumption patterns and contribute to science renewal by producing new knowledge supported by interdisciplinary dialogue and methodological development.