Global and Personal App Networks: Characterizing Social Relations among Mobile Apps

With the flourish of mobile computing, mobile Apps dominate the daily lives of users. Focusing on the social relations among Apps, this paper makes an empirical study on constructing the Global App Network (GAN) in terms of three types of inter-App relations (i.e., intent-based, semantics correlation based, and similarity-based ones), recovering Personal App Network (PAN) in terms of App usage log of each user, and exploring the characteristics of GAN and PAN. The study is based on two real-world datasets: the first one includes thousands of Apps collected from a real-world Android App store, and the second one contains 2-month App usage logs of 40 volunteers. Several interesting phenomena are observed from the study, such as (1) a large portion of implicit inter-App relations that are welcome by massive users are actually ignored by App developers, (2) some explicit relations proactively designed by App developers are actually not frequently used by users, (3) although there is a certain commonness among PANs of different users, each PAN shows a significant personalized pattern which delineates the individualized behaviors of a user. These conclusions are of significance to bi-directional App recommendations, i.e., to recommend neglected inter-App relations to App developers, and, to recommend common and popular inter-App relations to users.