The Impact of Covid-19 on Smartphone Usage

Show simple item record

dc.contributor.author Li, Tong
dc.contributor.author Zhang, Mingyang
dc.contributor.author Li, Yong
dc.contributor.author Lagerspetz, Eemil
dc.contributor.author Tarkoma, Sasu
dc.contributor.author Hui, Pan
dc.date.accessioned 2021-12-01T06:20:03Z
dc.date.available 2021-12-01T06:20:03Z
dc.date.issued 2021-12-01
dc.identifier.citation 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
dc.identifier.other PURE: 163130799
dc.identifier.other PURE UUID: 187bd4c0-2b9c-4d4e-9294-5ad56e6bc087
dc.identifier.other Scopus: 85104678631
dc.identifier.other WOS: 000720519000007
dc.identifier.other ORCID: /0000-0002-4343-703X/work/104025023
dc.identifier.other ORCID: /0000-0003-3875-8135/work/104088869
dc.identifier.uri http://hdl.handle.net/10138/336963
dc.description.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. en
dc.format.extent 11
dc.language.iso eng
dc.relation.ispartof IEEE internet of things journal
dc.rights unspecified
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 113 Computer and information sciences
dc.subject COVID-19
dc.subject Wireless fidelity
dc.subject Correlation
dc.subject Data collection
dc.subject North America
dc.subject Batteries
dc.subject Sensors
dc.subject Correlations
dc.subject Covid-19
dc.subject outbreak stage inference
dc.subject smartphone usage
dc.title The Impact of Covid-19 on Smartphone Usage en
dc.type Article
dc.contributor.organization Department of Computer Science
dc.contributor.organization Content-Centric Structures and Networking research group / Sasu Tarkoma
dc.contributor.organization Helsinki Institute for Information Technology
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1109/JIOT.2021.3073864
dc.relation.issn 2327-4662
dc.rights.accesslevel openAccess
dc.type.version acceptedVersion

Files in this item

Total number of downloads: Loading...

Files Size Format View
COVID19Carat_Final.pdf 9.148Mb PDF View/Open

This item appears in the following Collection(s)

Show simple item record