Understanding User Behavior in Spotify

被引：0

作者：

Zhang, Boxun ^{[1
]}

Kreitz, Gunnar ^{[2
]}

Isaksson, Marcus ^{[2
]}

Ubillos, Javier ^{[2
]}

Urdaneta, Guido

Pouwelse, Johan A. ^{[1
]}

Epema, Dick ^{[1
]}

机构：

[1] Delft Univ Technol, NL-2600 AA Delft, Netherlands

[2] KTH Royal Inst Technol, Stockholm, Sweden

来源：

2013 PROCEEDINGS IEEE INFOCOM | 2013年

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：220 / 224

页数：5