The Effect of Attribute-based Cultural Networks on Evaluation Outcomes in Popular Music

• In Event: 202 - Regular Session. Popular Culture

Abstract

In this paper we leverage recent developments in the way scholars access, collect, and measure cultural data 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 analysis suggests that cultural attributes matter, beyond the effects of artist familiarity, genre affiliation, and social influence. We also find evidence that the relational patterns formed between songs’ with shared attributes—what we call cultural networks—play an important role in determining how songs move up or down the charts. Songs that sound too much like their peers receive a performance discount, while those that are optimally differentiated are more likely to appear atop the charts. By recognizing that culture has its own sphere of influence that is distinct from the actors who produce and consume it, we reconsider some of the basic mechanisms that drive cultural consumption.

Authors

• Noah Askin, INSEAD

• Michael Mauskapf, Northwestern University