Why Some Old Songs Are Still Evergreen Even Today?
Cultural heritage; Deep learning; Evergreen songs; Graph neural networks; Human emotions; Music history; MusicBERT
The enduring appeal of old songs across generations raises questions about the factors contributing to their timelessness. This research investigates these factors using a deep learning framework that integrates MusicBERT, a model for symbolic music understanding, with Graph Neural Networks (GNNs). By analyzing a dataset of song features, including lyrics, melody, rhythm, and emotional tone, the study identifies patterns associated with the evergreen status of songs. Key findings emphasize cultural significance, emotional resonance, and universal themes as critical contributors to their lasting popularity. The research offers novel insights into the intersection of music, culture, and technology, with implications for music production, distribution, and cultural heritage preservation. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Greeshma, N.; Iyer, Lakshmi Shankar; Sophia Shalini, G.B.
Smart Innovation, Systems and Technologies;Volume;121 SIST;pp.497-509
Springer Science and Business Media Deutschland GmbH
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1007/978-981-96-6254-8_38 https://www.scopus.com/pages/publications/105018907021?origin=resultslist
Greeshma N., School of Business and Management, Christ University, Bangalore, India; Iyer L.S., School of Business and Management, Christ University, Bangalore, India; Sophia Shalini G.B., School of Business and Management, Christ University, Bangalore, India