Inferred network dataset.

We apply the independent cascade network inference model to a large database of music videos to infer the structure of the global network of music diffusion. The derived network reveals an intricate topology–fully interconnected, exhibiting a modular structure, and characterized by asymmetric links. We explore the relationship between the identified bilateral cultural diffusion pathways and the geographical and cultural distances among countries, and key socioeconomic interactions such as international trade and migration. Additionally, we use a gravity model to ascertain the factors contributing to both the formation and the intensity of the estimated diffusion channels between countries. Our findings reveal that cultural, geographical, and historical factors serve as primary drivers of musical diffusion, downplaying the importance of economic factors. This study posits that these elements exert considerable force in shaping musical preferences across nations, making the emergence of a homogeneous global musical culture improbable. This exploration adds valuable insights to the discourse on the globalization of music and its potential cultural implications.