期刊
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
卷 24, 期 2, 页码 937-966出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/COMST.2022.3163176
关键词
Mobile applications; Data collection; Monitoring; Data analysis; Computer science; Tutorials; Stakeholders; Smartphone device; mobile app; app usage; behavior analysis; data mining
资金
- National Key Research and Development Program of China [2020YFA0711403]
- National Natural Science Foundation of China [61972223, 61971267, 62171260, U1936217, U20B2060, U21B2036]
- International Postdoctoral Exchange Fellowship Program (Talent-Introduction Program) [YJ20210274]
- Academy of Finland [319669, 319670, 325570, 326305, 325774, 335934]
- NSF [CNS-2107216, CNS-2128368]
- Academy of Finland (AKA) [325774, 325774, 326305, 319669, 319670] Funding Source: Academy of Finland (AKA)
This article provides a comprehensive review of recent research on smartphone app usage analysis. It covers data collection methods, as well as studies in the app domain, user domain, and smartphone domain. The research reveals the connections between users, apps, and smartphones through the collection and analysis of app usage traces, and highlights challenges and future directions in this field.
As smartphones have become indispensable personal devices, the number of smartphone users has increased dramatically over the last decade. These personal devices, which are supported by a variety of smartphone apps, allow people to access Internet services in a convenient and ubiquitous manner. App developers and service providers can collect fine-grained app usage traces, revealing connections between users, apps, and smartphones. We present a comprehensive review of the most recent research on smartphone app usage analysis in this survey. Our survey summarizes advanced technologies and key patterns in smartphone app usage behaviors, all of which have significant implications for all relevant stakeholders, including academia and industry. We begin by describing four data collection methods: surveys, monitoring apps, network operators, and app stores, as well as nine publicly available app usage datasets. We then systematically summarize the related studies of app usage analysis in three domains: app domain, user domain, and smartphone domain. We make a detailed taxonomy of the problem studied, the datasets used, the methods used, and the significant results obtained in each domain. Finally, we discuss future directions in this exciting field by highlighting research challenges.
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