The role of network structure in music consumption

Abstract

Inundated with the massive influx of new songs and artists, today`s music industry is faced with notoriously capricious consumers. The short attention span of music consumers threatens life of musicians, and therefore, the ability to build and retain a stable fan base has now become more critical to survive in the market. Loyal fans are beneficial as they are more likely to remember musicians, make additional purchases (e.g. concert tickets), and promote music across peers via positive word-of-mouth. For music is consumed in a social context these days, this study investigates the impact of neighborhood and network structure on music consumption behaviors in Twitter. The purpose of this study is twofold. First, the determinants of a musician`s survival are examined, focused on the role of user-specific network topology within fan community in sustaining fan activity. Econometrically, we apply an Accelerated Failure Time Model (AFTM) with log-logistic specification using individual-level Twitter data on fan activities in 2011. Focusing on the value of cultivating relationships among customers, we pay attention to how music audition program`s contestants differ from ordinary musicians in their fan community characteristics. Second, we explore the impact of network topology in music consumption in different stages of musician diffusion. We apply a Spatial Error Model (SEM) to control unobserved spatial correlation, or interactions among fans. Specifically, this analysis identifies the factors that influence fan activities in the first and second months of the debut of musicians. From the two analyses, we found that fans of ordinary musicians obtain a higher level of utility by sharing common object of fandom with their neighbors, but the extent of perceptual boundary for such neighbors tends to be local. Specifically, high global clustering deters fans from engaging in fan activities within a short interval, while high local clustering encourages them to express ...