The algorithmic network imaginary: How music artists understand and experience their algorithmically constructed networks

Abstract

In this article we develop the concept of “algorithmic network imaginary” to understand how musicians imagine and relate to the networks of “related artists” they are algorithmically sorted into on Spotify. To address this question, we collected data on the related artist networks of 22 musicians constructed by Spotify’s Fans Also Like feature and conducted semi-structured, in-depth interviews with each musician. We used the Qualitative Structural Analysis method for data analysis. Our findings provide insight into what musicians think Fans Also Like is and is for, and reveals how cultural creators understand and experience their algorithmic networks. More broadly, they provide insights into how social actors perceive, understand, and experience their algorithmically constructed peer networks.