Mining Device-Specific Apps Usage Patterns from Large-Scale Android Users
Huoran Li, Xuan Lu

TL;DR
This study analyzes how different Android device models influence user app behaviors, revealing significant correlations and behavioral patterns across a large-scale user dataset from China.
Contribution
It provides the first large-scale empirical analysis of device-specific app usage patterns using detailed longitudinal data from over 700,000 users.
Findings
Device models significantly influence app selection and abandonment.
Lower-end devices are associated with higher spending and more cellular data usage.
Users with different devices show diverse preferences for competing apps.
Abstract
When smartphones, applications (a.k.a, apps), and app stores have been widely adopted by the billions, an interesting debate emerges: whether and to what extent do device models influence the behaviors of their users? The answer to this question is critical to almost every stakeholder in the smartphone app ecosystem, including app store operators, developers, end-users, and network providers. To approach this question, we collect a longitudinal data set of app usage through a leading Android app store in China, called Wandoujia. The data set covers the detailed behavioral profiles of 0.7 million (761,262) unique users who use 500 popular types of Android devices and about 0.2 million (228,144) apps, including their app management activities, daily network access time, and network traffic of apps. We present a comprehensive study on investigating how the choices of device models affect…
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Taxonomy
TopicsGreen IT and Sustainability · Mobile and Web Applications · Innovative Human-Technology Interaction
