  One of the fundamental questions of cultural evolutionary research is how
individual-level processes scale up to generate population-level patterns.
Previous studies in music have revealed that frequency-based bias (e.g.
conformity and novelty) drives large-scale cultural diversity in different ways
across domains and levels of analysis. Music sampling is an ideal research
model for this process because samples are known to be culturally transmitted
between collaborating artists, and sampling events are reliably documented in
online databases. The aim of the current study was to determine whether
frequency-based bias has played a role in the cultural transmission of music
sampling traditions, using a longitudinal dataset of sampling events across
three decades. Firstly, we assessed whether turn-over rates of popular samples
differ from those expected under neutral evolution. Next, we used agent-based
simulations in an approximate Bayesian computation framework to infer what
level of frequency-based bias likely generated the observed data. Despite
anecdotal evidence of novelty bias, we found that sampling patterns at the
population-level are most consistent with conformity bias.
