Sociological research highlights the importance of social influence in the formation of individual preferences and the propagation of aggregate trends. Social scientists have long recognized the importance of social influence, particularly in opaque settings such as financial markets, political elections, and cultural industries. Within the sociological study of markets, cultural industries have received particular attention, because they typically lack objective standards of valuation. Consequently, market success often depends on social interactions that signal availability, excellence, and the potential for shared consumption.
Due to the uncertainty of cultural markets, offerings maintained by social valuation are often more likely to be considered for consumption which, in turn, increases potential audience size. Situations in which people react to an environment that consists of other individuals who are reacting likewise are likely to give rise to cumulative-advantage processes. These dynamics typically result in highly skewed aggregate outcomes (“emergence of stars”) which not necessarily reflect inherent product attributes (“bad bestsellers”). Such environments provide valuable testing grounds for theories of socially influenced behavior, with complex dynamics that can generate hard-to-predict collective outcomes.
At IAS we study these and related phenomena in book markets and the film industry. More recently, the advent of global online music platforms allows the study of cultural dynamics on a very large scale. Scrutinizing cultural choice at Spotify.com, a leading online music platform, we formulate and test theories of peer influence and social contagion among interconnected consumers of music to gain understanding of the mechanisms underlying the emergence of hits, the establishment of new artists and genres, and cultural change more generally.
Sales distribution for fiction books (Germany, 2001-06). Histogram and log-log plot with power law exponent β = 1.96 in the upper tail.
Two-dimensional representation of cultural taste profiles for a subset of 50,000 Spotify users. Each dot represents a user, and the color indicates the particular taste cluster each user was assigned to by a k-means algorithm.