Characterizing Smartphone Usage Patterns from Millions of Android Users

ABSTRACT

he prevalence of smart devices has promoted the popular- ity of mobile applications (a.k.a. apps) in recent years. A number of interesting and important questions remain unan- swered, such as why a user likes/dislikes an app, how an app becomes popular or eventually perishes, how a user selects apps to install and interacts with them, how frequently an app is used and how much traffic it generates, etc. This paper presents an empirical analysis of app usage behaviors collected from millions of users of Wandoujia, a leading An- droid app marketplace in China. The dataset covers two types of user behaviors of using over 0.2 million Android apps, including (1) app management activities (i.e., installa- tion, updating, and uninstallation) of over 0.8 million unique users and (2) app network traffic from over 2 million unique users. We explore multiple aspects of such behavior data and present interesting patterns of app usage. The results provide many useful implications to the developers, users, and disseminators of mobile apps.

References

1. A. Apaolaza, S. Harper, and C. Jay. Understanding users in the wild. In Proc. of W4A, page 13, 2013.
2. M. Böhmer, B. Hecht, J. Schöning, A. Krüger, and G. Bauer. Falling asleep with angry birds, Facebook and Kindle: a large scale study on mobile application usage. In Proc. of MobileHCI, pages 47--56, 2011.
3. M. Böhmer and A. Krüger. A study on icon arrangement by smartphone users. In Proc. of CHI, pages 2137--2146, 2013.
4. N. Chen, J. Lin, S. C. H. Hoi, X. Xiao, and B. Zhang. AR-miner: mining informative reviews for developers from mobile app marketplace. In Proc. of ICSE, pages 767--778, 2014.
5. T. M. T. Do and D. Gatica-Perez. Where and what: Using smartphones to predict next locations and applications in daily life. Pervasive and Mobile Computing, 12:79--91, 2014.
6. H. Falaki, D. Lymberopoulos, R. Mahajan, S. Kandula, and D. Estrin. A first look at traffic on smartphones. In Proc. of IMC, pages 281--287, 2010.
7. H. Falaki, R. Mahajan, S. Kandula, D. Lymberopoulos, R. Govindan, and D. Estrin. Diversity in smartphone usage. In Proc. of MobiSys, pages 179--194, 2010.
8. B. Fu, J. Lin, L. Li, C. Faloutsos, J. I. Hong, and N. M. Sadeh. Why people hate your app: making sense of user feedback in a mobile app store. In Proc. of KDD, pages 1276--1284, 2013.
9. J. Huang, F. Qian, Z. M. Mao, S. Sen, and O. Spatscheck. Screen-off traffic characterization and optimization in 3g/4g networks. In Proc. of IMC, pages 357--364, 2012.
10. Z. Liao, S. Li, W. Peng, P. S. Yu, and T. Liu. On the feature discovery for app usage prediction in smartphones. In Proc. of ICDM, pages 1127--1132, 2013.
11. Z. Liao, Y. Pan, W. Peng, and P. Lei. On mining mobile apps usage behavior for predicting apps usage in smartphones. In Proc. of CIKM, pages 609--618, 2013.
12. S. L. Lim, P. J. Bentley, N. Kanakam, F. Ishikawa, and S. Honiden. Investigating country differences in mobile app user study behavior and challenges for software engineering. IEEE Transactions on Software Engineering, 40(5):40--64, 2014.
13. R. Montoliu, J. Blom, and D. Gatica-Perez. Discovering places of interest in everyday life from smartphone data. Multimedia Tools Appl., 62(1):179--207, 2013.
14. M. E. J. Newman. Power Laws, Pareto Distributions and Zipf's Law. Contemporary Physics, 46:323, 2005.
15. R. Pandita, X. Xiao, W. Yang, W. Enck, and T. Xie. WHYPER: Towards automating risk assessment of mobile applications. In USENIX Security, pages 527--542, 2013.
16. A. Patro, S. K. Rayanchu, M. Griepentrog, Y. Ma, and S. Banerjee. Capturing mobile experience in the wild: a tale of two apps. In Proc. of CoNEXT, pages 199--210, 2013.
17. T. Petsas, A. Papadogiannakis, M. Polychronakis, E. P. Markatos, and T. Karagiannis. Rise of the planet of the apps: a systematic study of the mobile app ecosystem. In Proc. of IMC, pages 277--290, 2013.
18. A. Rahmati, C. Tossell, C. Shepard, P. T. Kortum, and L. Zhong. Exploring iphone usage: the influence of socioeconomic differences on smartphone adoption, usage and usability. In Proc. of MobileHCI, pages 11--20, 2012.
19. A. Rahmati and L. Zhong. Studying smartphone usage: Lessons from a four-month field study. IEEE Trans. Mob. Comput., 12(7):1417--1427, 2013.
20. A. A. Sani, Z. Tan, P. Washington, M. Chen, S. Agarwal, L. Zhong, and M. Zhang. The wireless data drain of users, apps, & platforms. Mobile Computing and Communications Review, 17(4):15--28, 2013.
21. C. Shin and A. K. Dey. Automatically detecting problematic use of smartphones. In Proc. of Ubicomp, pages 335--344, 2013.
22. C. Shin, J. Hong, and A. K. Dey. Understanding and prediction of mobile application usage for smart phones. In Proc. of Ubicomp, pages 173--182, 2012.
23. C. Tossell, P. T. Kortum, A. Rahmati, C. Shepard, and L. Zhong. Characterizing web use on smartphones. In Proc. of CHI, pages 2769--2778, 2012.
24. Q. Xu, J. Erman, A. Gerber, Z. M. Mao, J. Pang, and S. Venkataraman. Identifying diverse usage behaviors of smartphone apps. In Proc. of IMC, pages 329--344, 2011.
25. B. Yan and G. Chen. Appjoy: personalized mobile application discovery. In Proc. of MobiSys, pages 113--126, 2011.

Index Terms

• General and reference

  • Cross-computing tools and techniques

    • Measurement

    • Performance

• Social and professional topics

  • Professional topics

    • Management of computing and information systems

      • Software management

        • Software selection and adaptation

• Software and its engineering

  • Software organization and properties

    • Extra-functional properties

      • Software performance