Understanding Diverse Usage Patterns from Large-Scale Appstore-Service Profiles
| Autor: | Feng Feng, Xuanzhe Liu, Hong Mei, Xuan Lu, Huoran Li, Tao Xie, Qiaozhu Mei |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mobile deep linking
business.industry Computer science 020206 networking & telecommunications 020207 software engineering 02 engineering and technology App store Electronic mail World Wide Web Empirical research Software deployment 0202 electrical engineering electronic engineering information engineering Mobile telephony Android (operating system) business Mobile device Software |
| Zdroj: | IEEE Transactions on Software Engineering. 44:384-411 |
| ISSN: | 1939-3520 0098-5589 |
| DOI: | 10.1109/tse.2017.2685387 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|