The Shrinking Sweet Spot: How Algorithms, Institutions, and Social Priors Shape Musical Ecosystems
Fabio Lokwani Di Matteo, Pier Luigi Sacco

TL;DR
This paper models musical taste as an evolving learning process influenced by algorithms, institutions, and social factors, explaining diversity and homogenization in musical ecosystems across nations.
Contribution
It introduces a dynamic, sequential choice model based on active inference, integrating economic, social, and algorithmic influences on musical preferences.
Findings
Algorithmic curation reduces diversity beyond a nonlinear threshold.
Institutional structures influence dominance and competition among musical ecosystems.
Cultural capital helps maintain diversity against homogenization.
Abstract
Why do some national music markets sustain a rich musical diversity whereas others converge on mostly formulaic output? The existing models of cultural consumption (superstar economics, rational addiction, Bayesian social learning) each capture part of the answer, but none can explain how exposure, social influence, institutional gatekeeping, and algorithmic curation interact to shape what listeners come to prefer. We address this gap by modeling musical taste as a learning process rather than a fixed parameter: a listener's evaluative disposition evolves with each encounter, shaped by the balance between the comfort of the familiar and the reward of the new. Drawing on the active inference framework from cognitive science, we formalize this as a sequential choice model in which preferences, information, and the consumption environment co-evolve, and show how the framework nests and…
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