Professor Juyong Park of KAIST’s Graduate School of Culture Technology and his research team recently published the result of their study (“Topology and Evolution of the Network of Western Classical Music Composers”) on the dynamics of how classical music is created, stylized and disseminated in EPJ Data Science online.
Copyright : KAIST
The KAIST team used big-data analysis and modelling technique to examine the complex, undercurrent network of classical music composers, which was constructed from the large volume of compact disc (CD) recordings data collected from an online retailer, ArkivMusic, and a music reference website, AllMusicGuide.
The study discovered that the basic characteristics of composers’ network are similar to many real-world networks, including the small-world property, the existence of a giant component, high clustering, and heavy-tailed degree distributions. The research team also found that composers collaborated and influenced each other and that composers’ networks grew over time.
The research showed that consumers of classical music CDs tend to listen together to the music of a certain group of different composers, offering a useful tool to understand how the music style and market develops. Based on this, the research team predicted the future of the classical music market would be centered on top composers, while maintaining diversity due to the growing number of new composers.
Professor Park said, “In recent years, technology greatly affects the way we consume culture and art. Accordingly, we see more and more artists and institutions try to incorporate technology into their creative process, and this will lead us to larger- and higher-quality data that can allow us to learn more about culture and art. The quantitative methodology we have demonstrated in our research will give us an opportunity to explore the nature of art and literature in novel ways.”
The European Physical Journal (EPJ) comprises a series of peer-reviewed journals, eleven in total, which cover physics and related subjects such as The Large Hadron Collider, condensed matter, particles, soft matter and biological physics. The EPJ Data Science is the latest journal launched by EPJ
