Di Marco · Scientific reports 2026 · computational corpus analysis / network science study · n=approximately 20,000 musical pieces

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

Cited 1 times in the scientific literature.

Level 4 - case-series / case-control

Level is by design analogy (observational computational corpus analysis of historical musical data, not clinical CEBM).

PubMed 42026097 · doi:10.1038/s41598-026-42872-7 · record verified 2026-08-29

What was done

Researchers analyzed a dataset of approximately 20,000 MIDI transcriptions of Western music spanning six macro-genres and nearly four centuries. Each musical piece was modeled as a weighted directed network to quantitatively evaluate topological, melodic, and harmonic characteristics over time.

What was found

Different musical genres exhibited distinct network topologies and musical properties. Temporal analysis demonstrated systematic shifts over time toward reduced structural complexity and increased similarity in melodic and harmonic patterns across genres, with older complex genres (Classical and Jazz) showing structural convergence toward patterns observed in more recent genres. The abstract provides no specific numerical values, effect sizes, or statistical test statistics.

Why it matters

This study provides a large-scale computational framework using network science to track long-term cultural evolution and structural homogenization in Western music over 400 years.

Limits

The abstract lacks explicit quantitative values, specific network metrics, and effect sizes. Findings are confined to Western musical traditions and rely on the representativeness and accuracy of MIDI transcriptions.

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