P5-07: Towards Quantifying the Strength of Music Scenes Using Live Event Data
Zhou, Michael*, McGraw, Andrew, Turnbull, Douglas R
Subjects (starting with primary): Evaluation, datasets, and reproducibility -> novel datasets and use cases ; Philosophical and ethical discussions -> legal and societal aspects of MIR ; MIR fundamentals and methodology -> web mining, and natural language processing ; Applications -> music and health, well-being and therapy
Presented Virtually: 4-minute short-format presentation
There are many benefits for a community when there is a vibrant local music scene (e.g., increased mental & physical well-being, increased economic activity) and there are many factors that contribute to an environment in which a live music scene can thrive (e.g., available performance spaces, helpful government policies). In this paper, we explore using an estimate of the live music event rate (LMER) as a rough indicator to measure the strength of a local music scene. We define LMER as the number of music shows per 100,000 people per year and then explore how this indicator is (or is not) correlated with 28 other socioeconomic indicators. To do this, we analyze a set of 308,051 music events from 2019 across 1,139 cities in the United States. Our findings reveal that factors related to transportation (e.g., high walkability), population (high density), economics (high employment rate), age (high proportion of individuals age 20-29), and education (bachelor’s degree or higher) are strongly correlated with having a high number of live music events. Conversely, we did not find statistically significant evidence that other indica- tors (e.g., racial diversity) are correlated.