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 user behaviors such as the adoption of app stores, app selection and abandonment, data plan usage, online time length, the tendency to use paid/free apps, and the preferences to choosing competing apps. Some significant correlations between device models and app usage are derived from appstore big data, leading to important findings on the various user behaviors. For example, users owning different device models have a substantial diversity of selecting competing apps, and users owning lower-end devices spend more money to purchase apps and spend more time under cellular network.
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Notes
- 1.
In this paper, the term “device model” refers to the device with specific product type with hardware specifications, e.g., Samsung N7100, N9100, Xiaomi 3s, and so on.
- 2.
Our study has been approved by the research ethnics board of the Institute of Software, Peking University. The data is legally used without leaking any sensitive information. The details of user privacy protection are presented later in the data set description. We plan to open the data set when the manuscript is published.
- 3.
- 4.
Visit its official site via http://www.wandoujia.com.
- 5.
http://shouji.jd.com, Jd is the largest e-commerce for electronic devices in China.
- 6.
Due to space limit, the details of how Wandoujia management app works can be referred to our previous work [11].
- 7.
One co-author is the head of Wandoujia product. He supervised the process of data collection and de-identification.
- 8.
https://itunes.apple.com/us/app/dong-dong-gou-wu-zhu-shou/id868597002?mt=8, is an app for inquiring history price of products on Jd.
- 9.
http://www.xitie.com, is a website for inquiring price history of products on popular e-commerce sites.
- 10.
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Acknowledgement
This work was supported by the National Key R&D Program under the grant number 2018YFB1004800, the National Natural Science Foundation of China under grant numbers 61725201, 61528201, 61529201, and a Google Faculty Award. We thank Wenlong Mou for assistance with statistical analysis in this project, and for comments that greatly improved the manuscript.
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Li, H., Liu, X., Mei, H., Mei, Q. (2018). Mining Device-Specific Apps Usage Patterns from Appstore Big Data. In: Xu, Z., Gao, X., Miao, Q., Zhang, Y., Bu, J. (eds) Big Data. Big Data 2018. Communications in Computer and Information Science, vol 945. Springer, Singapore. https://doi.org/10.1007/978-981-13-2922-7_4
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