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<p>Music has always been central to human culture, reflecting and shaping traditions, emotions, and societal changes. Therefore, analysing the quantitative properties of musical compositions can provide insights into specific aspects of human cultural evolution. In this study, we conduct a large-scale analysis of approximately 20,000 musical pieces rooted in Western musical practices. The resulting dataset encompasses MIDI transcriptions of works from six major macro-genres, spanning nearly four centuries of musical history. We model musical composition as weighted directed networks, enabling a systematic investigation of melodic and harmonic properties through a network-based representation of music. Our results show that different genres have distinct topological and musical properties, providing valuable insights into the origins of their differences. Moreover, a temporal analysis reveals systematic changes in network-based measures, suggesting a trend toward increasing similarity and reduced complexity in the melodic and harmonic structures. Notably, within this analytical perspective, even long-established and structurally complex genres such as Classical and Jazz display patterns that are increasingly comparable to those of more recent genres.</p>

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Decoding the evolution of melodic and harmonic structure of Western music through the lens of network science

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月23日

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  • Niccolò Di Marco,
  • Edoardo Loru,
  • Alessandro Galeazzi,
  • Matteo Cinelli,
  • Walter Quattrociocchi

摘要

Music has always been central to human culture, reflecting and shaping traditions, emotions, and societal changes. Therefore, analysing the quantitative properties of musical compositions can provide insights into specific aspects of human cultural evolution. In this study, we conduct a large-scale analysis of approximately 20,000 musical pieces rooted in Western musical practices. The resulting dataset encompasses MIDI transcriptions of works from six major macro-genres, spanning nearly four centuries of musical history. We model musical composition as weighted directed networks, enabling a systematic investigation of melodic and harmonic properties through a network-based representation of music. Our results show that different genres have distinct topological and musical properties, providing valuable insights into the origins of their differences. Moreover, a temporal analysis reveals systematic changes in network-based measures, suggesting a trend toward increasing similarity and reduced complexity in the melodic and harmonic structures. Notably, within this analytical perspective, even long-established and structurally complex genres such as Classical and Jazz display patterns that are increasingly comparable to those of more recent genres.