Measuring the Significance of the Geographic Flow of Music

TL;DR

This paper evaluates the predictive power of geographic leader-follower relationships in musical preferences, finding only modest improvements, which suggests these relationships are weak.

Contribution

It provides an empirical assessment of the significance of geographic flow in music preferences through predictive modeling.

Findings

Linear models improve predictions by about 5% using past preferences from other cities.

Leader-follower relationships in music preferences are weak.

Previous assumptions about strong geographic influence are not strongly supported.

Abstract

In previous work, our results suggested that some cities tend to be ahead of others in their musical preferences. We concluded that work by noting that to properly test this claim, we would try to exploit the leader-follower relationships that we identified to make predictions. Here we present the results of our predictive evaluation. We find that information on the past musical preferences in other cities allows a linear model to improve its predictions by approx. 5% over a simple baseline. This suggests that at best, previously found leader-follower relationships are rather weak.