Eita Nakamura, Kunihiko Kaneko, Statistical Evolutionary Laws in Music Styles, arXiv:1809.05832v1 [physics.soc-ph].
If a cultural feature is transmitted over generations and exposed to stochastic selection when spreading in a population, its evolution may be governed by statistical laws, as in the case of genetic evolution. Music exhibits steady changes of styles over time, with new characteristics developing from traditions. Recent studies have found trends in the evolution of music styles, but little is known about quantitative laws and theories. Here we analyze Western classical music data and find statistical evolutionary laws. For example, distributions of the frequencies of some rare musical events (e.g. dissonant intervals) exhibit steady increase in the mean and standard deviation as well as constancy of their ratio. We then study an evolutionary model where creators learn their data-generation models from past data and generate new data that will be socially selected by evaluators according to novelty and typicality. The model reproduces the observed statistical laws and its predictions are in good agreement with real data. We conclude that some trends in music culture can be formulated as statistical evolutionary laws and explained by the evolutionary model incorporating statistical learning and the novelty-typicality bias.
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