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Engagement-based curation and the evolution of taste

Bibliographic Data

ID21579136
AuthorsSamsun Knight (0009-0002-7996-4816, University of Toronto, corresponding author)
Year2026
Volume50
Issue2
Pages399-444
Publication date2026-06-01
Open AccessYes
TypeARTICLE
VenueJournal of Cultural Economics (JOURNAL)
Journal identifiersISSN: 0885-2545 • E-ISSN: 1573-6997
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s10824-026-09591-3
OpenAlexW7154726525
LanguageEN
References cited35

We develop a dynamic model of how engagement-driven curation, such as Spotify’s algorithmic curation of playlists or Netflix’s personalized menus of TV shows, shapes the evolution of aesthetic tastes. Building on the canonical consumption capital model of Becker et al. (1988), we introduce two innovations: non-monotonic returns to familiarity, where moderate exposure to a style enhances appreciation but excessive exposure causes boredom; and curator-controlled exposure, where engagement-maximizing intermediaries determine which content consumers encounter. We show that when curators treat consumers’ familiarity as exogenous, failing to recognize it as shaped by their own past promotional choices, they can become trapped in inefficient equilibria with self-confirming beliefs, even though they may have high predictive accuracy for any given recommendation. Second, even when curators track familiarity as an endogenous state variable, they structurally underexplore when their evaluation horizons are short relative to long-run taste evolution timescales. We derive welfare implications, characterize comparative statics, and show that in both cases, lower prediction accuracy in curation can be welfare-improving

Cultural economics · Taste · The arts · Artistic and Creative Research · Diverse Musicological Studies · Multisensory perception and integration

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Highly citedNo
Open DOIOpen Access
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