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Understanding the Long-Term Evolution of Mobile App Usage

Tong LiDepartment of Computer Science, University of Helsinki, Helsinki, FinlandYali FanSchool of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, ChinaYong LiDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, ChinaSasu TarkomaDepartment of Computer Science, University of Helsinki, Helsinki, FinlandPan HuiComputational Media and Arts Trust, Hong Kong University of Science and Technology (Guangzhou), China
2021en
ABI

Аннотация

The prevalence of smartphones has promoted the popularity of mobile apps in recent years. Although significant effort has been made to understand mobile app usage, existing studies are based primarily on short-term datasets with a limited time span, e.g., a few months. Therefore, many basic facts about the long-term evolution of mobile app usage are unknown. In this paper, we study how mobile app usage evolves over a long-term period. We first introduce an app usage collection platform named carat, from which we have gathered app usage records of 1,465 users from 2012 to 2017. We then conduct the first study on the long-term evolution processes on a macro-level, i.e., app-category, and micro-level, i.e., individual app. We discover that, on both levels, there is a growth stage enabled by the introduction of new technologies. Then there is a plateau stage caused by high correlations between app categories and a Pareto effect in individual app usage, respectively. Additionally, the evolution of individual app usage undergoes an elimination stage due to fierce intra-category competition. The inter-diversity of app-category and individual app usage exhibits opposing trends: app-category usage assimilates while individual app usage diversifies. Nevertheless, the intra-diversity of both app-category and app usage declines over time. Also, we demonstrate the country barriers of app category usage. We further investigate how different demographics affect the evolutionary processes of app usage. Our study provides useful implications for app developers, market intermediaries, and service providers.

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