Understanding user behavior in Spotify
2013 (English)In: 2013 Proceedings - IEEE INFOCOM, 2013, 220-224 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
2013. 220-224 p.
, Proceedings - IEEE INFOCOM, ISSN 0743-166X
Arrival patterns, Daily variations, Music streaming, Peer-assisted, System Dynamics, User behaviors, User sessions, Worldwide popularity, Behavioral research
Computer and Information Science Human Computer Interaction
IdentifiersURN: urn:nbn:se:kth:diva-133803DOI: 10.1109/INFCOM.2013.6566767ISI: 000326335200052ScopusID: 2-s2.0-84883126992ISBN: 978-146735946-7OAI: oai:DiVA.org:kth-133803DiVA: diva2:676555
32nd IEEE Conference on Computer Communications, IEEE INFOCOM 2013; Turin, Italy, 14-19 April 2013
QC 201312062013-12-062013-11-112014-01-28Bibliographically approved