Listening in Lockdown

The Covid-19 pandemic has brought with it unprecedented shifts in the way that we go about our everyday lives.

It has altered our interaction socially and isolated us physically from many of the people, places and pastimes that we love. As such we may have become even more reliant on streaming technology as a means to entertain us.

Can our use and choice of streaming material reveal our experience of living under the cloud of Covid-19? What would analysis of our streaming material suggest about mental health, mood states, and attitudinal approaches to the local and worldwide health crisis? And can a methodological framework be constructed to allow such questions to be addressed more readily in future?

Using Spotify’s API to gain direct access to user-created playlists that purport to be related to the pandemic (including terms like coronavirus, lockdown, quarantine etc.) we can analyze the structures of the playlists and the audio features of each track selected by users. We can build the ‘average’ playlist for the pandemic, but also find the extremes of where listeners habits took them, from defiant cheerfulness in the face of the virus to cathartic melancholy.

Blending big data (over 1 million tracks and 11 thousand playlists) and music psychology, we can begin to build a picture of how listening was shaped by Covid-19 and how our response to the virus may have been altered by our listening.

Integral to the project is the PhD work of Mimi (Katherine) O'Neill, studying for her doctorate at the University of York, Department of Music.