The Impact of Covid-19 on Smartphone Usage

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http://hdl.handle.net/10138/336963

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Li , T , Zhang , M , Li , Y , Lagerspetz , E , Tarkoma , S & Hui , P 2021 , ' The Impact of Covid-19 on Smartphone Usage ' , IEEE internet of things journal , vol. 8 , no. 23 , pp. 16723-16733 . https://doi.org/10.1109/JIOT.2021.3073864

Title: The Impact of Covid-19 on Smartphone Usage
Author: Li, Tong; Zhang, Mingyang; Li, Yong; Lagerspetz, Eemil; Tarkoma, Sasu; Hui, Pan
Contributor organization: Department of Computer Science
Content-Centric Structures and Networking research group / Sasu Tarkoma
Helsinki Institute for Information Technology
Date: 2021-12-01
Language: eng
Number of pages: 11
Belongs to series: IEEE internet of things journal
ISSN: 2327-4662
DOI: https://doi.org/10.1109/JIOT.2021.3073864
URI: http://hdl.handle.net/10138/336963
Abstract: The outbreak of Covid-19 changed the world as well as human behavior. In this article, we study the impact of Covid-19 on smartphone usage. We gather smartphone usage records from a global data collection platform called Carat, including the usage of mobile users in North America from November 2019 to April 2020. We then conduct the first study on the differences in smartphone usage across the outbreak of Covid-19. We discover that Covid-19 leads to a decrease in users' smartphone engagement and network switches, but an increase in WiFi usage. Also, its outbreak causes new typical diurnal patterns of both memory usage and WiFi usage. Additionally, we investigate the correlations between smartphone usage and daily confirmed cases of Covid-19. The results reveal that memory usage, WiFi usage, and network switches of smartphones have significant correlations, whose absolute values of Pearson coefficients are greater than 0.8. Moreover, smartphone usage behavior has the strongest correlation with the Covid-19 cases occurring after it, which exhibits the potential of inferring outbreak status. By conducting extensive experiments, we demonstrate that for the inference of outbreak stages, both Macro-F1 and Micro-F1 can achieve over 0.8. Our findings explore the values of smartphone usage data for fighting against the epidemic.
Subject: 113 Computer and information sciences
COVID-19
Wireless fidelity
Correlation
Data collection
North America
Batteries
Sensors
Correlations
Covid-19
outbreak stage inference
smartphone usage
Peer reviewed: Yes
Rights: unspecified
Usage restriction: openAccess
Self-archived version: acceptedVersion


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