Understanding Diverse Usage Patterns from Large-Scale Appstore-Service Profiles

Xuanzhe Liu, Huoran Li, Xuan Lu, Tao Xie, Qiaozhu Mei, Feng Feng, Hong Mei

Research output: Contribution to journalArticle

Abstract

The prevalence of smart mobile devices has promoted the popularity of mobile applications (a.k.a. apps). Supporting mobility has become a promising trend in software engineering research. This article presents an empirical study of behavioral service profiles collected from millions of users whose devices are deployed with Wandoujia, a leading Android app-store service in China. The dataset of Wandoujia service profiles consists of two kinds of user behavioral data from using 0.28 million free Android apps, including (1) app management activities (i.e., downloading, updating, and uninstalling apps) from over 17 million unique users and (2) app network usage from over 6 million unique users. We explore multiple aspects of such behavioral data and present patterns of app usage. Based on the findings as well as derived knowledge, we also suggest some new open opportunities and challenges that can be explored by the research community, including app development, deployment, delivery, revenue, etc.

Original languageEnglish (US)
Pages (from-to)384-411
Number of pages28
JournalIEEE Transactions on Software Engineering
Volume44
Issue number4
DOIs
StatePublished - Apr 1 2018

Keywords

  • Mobile apps
  • app store
  • user behavior analysis

ASJC Scopus subject areas

  • Software

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