Understanding user behavior in Spotify

TLDR

Spotify is a globally popular peer‑assisted music streaming service, yet little research has examined its user behavior. The study analyzes Spotify user behavior using a large 2010‑2011 dataset. The authors examined system dynamics such as session and playback patterns, individual user behavior across devices, and device‑switching patterns using the dataset. The analysis identified peak listening times and found that session length and downtime are correlated on single devices.

Abstract

Spotify is a peer-assisted music streaming service that has gained worldwide popularity in the past few years. Until now, little has been published about user behavior in such services. In this paper, we study the user behavior in Spotify by analyzing a massive dataset collected between 2010 and 2011. Firstly, we investigate the system dynamics including session arrival patterns, playback arrival patterns, and daily variation of session length. Secondly, we analyze individual user behavior on both multiple and single devices. Our analysis reveals the favorite times of day for Spotify users. We also show the correlations between both the length and the downtime of successive user sessions on single devices. In particular, we conduct the first analysis of the device-switching behavior of a massive user base.