The Effect of Attribute-based Cultural Networks on Selection Dynamics in Popular Music

In this paper we integrate insights from cultural sociology, network theory, and computer science to reexamine evaluation outcomes in popular music. Using web-based tools to construct a data set that distills songs’ musical content into a set of discrete attributes, we test whether and how these attributes affect a song’s performance on the Billboard Hot 100 charts. Our analyses suggest that cultural attributes matter, beyond the effects of artist familiarity, genre affiliation, and social influence. More specifically, we find evidence that cultural networks, or the relational patterns formed between songs’ with shared attributes, play an important role in determining songs’ popularity. Songs that sound too similar to contemporaneous songs tend to suffer, while those that are optimally differentiated are more likely to appear atop the charts. These results contribute to the growing literature on endogenous cultural effects, prompting us to reconsider some of the basic mechanisms that drive consumption behavior.