Demographics of mobile app usage: long-term analysis of mobile app usage

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Tu , Z , Cao , H , Lagerspetz , E , Fan , Y , Flores , H , Tarkoma , S , Nurmi , P & Li , Y 2021 , ' Demographics of mobile app usage: long-term analysis of mobile app usage ' , CCF Transactions on Pervasive Computing and Interaction , vol. 3 , pp. 235–252 .

Title: Demographics of mobile app usage: long-term analysis of mobile app usage
Author: Tu, Zhen; Cao, Hancheng; Lagerspetz, Eemil; Fan, Yali; Flores, Huber; Tarkoma, Sasu; Nurmi, Petteri; Li, Yong
Contributor organization: Department of Computer Science
Content-Centric Structures and Networking research group / Sasu Tarkoma
Helsinki Institute for Information Technology
Date: 2021
Language: eng
Number of pages: 18
Belongs to series: CCF Transactions on Pervasive Computing and Interaction
ISSN: 2524-521X
Abstract: In the past decade, mobile app usage has played an important role in our daily life. Existing studies have shown that app usage is intrinsically linked with, among others, demographics, social and economic factors. However, due to data limitations, most of these studies have a short time span and treat users in a static manner. To date, no study has shown whether changes in socioeconomic status or other demographics are reflected in long-term app usage behavior. In this paper, we contribute by presenting the first ever long-term study of individual mobile app usage dynamics and how app usage behavior of individuals is influenced by changes in socioeconomic demographic factors over time. Through a novel app dataset we collected, from which we extracted records of 1608 long-term users with more than 3-year app usage and their detailed socioeconomic attributes, we verify the stable correlation between user app usage and user socioeconomic attributes over time and identify a number of representative app usage patterns in connection with specific user attributes. On the basis, we analyze the long-term app usage dynamics and reveal that there is significant evolution in long-term app usage that 60–70% of users change their app usage patterns during the duration of more than 3 years. We further discover a variety of app pattern change modes and demonstrate that the long-term app usage behavior change reflects corresponding transition in socioeconomic attributes, such as change of civil status, family size, transition in job or economic status.
Subject: 113 Computer and information sciences
App usage
Long-term analysis
Economic attributes
User study
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: acceptedVersion

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