Refining smartphone usage analysis by combining crowdsensing and survey
Identifieur interne : 004060 ( Hal/Curation ); précédent : 004059; suivant : 004061Refining smartphone usage analysis by combining crowdsensing and survey
Auteurs : Vassili Rivron [France] ; Mohammad Irfan Khan [France] ; Simon Charneau [France] ; Isabelle Chrisment [France]Source :
Abstract
Crowdsensing has been used quite regularly in recent years to study smartphone usage. However context information associated with smartphone usage is mostly of the type geo-localisation, user mobility, temporal behavior etc. Furthermore most studies are not sufficiently user-centric i.e. don't consider the perception or cognitive aspects of the user. In this paper we collect data about social context and user perception via in-app and on-line questionnaires and show that when these are combined with crowdsensed data can help improve both sensing and survey and can be applied to interesting cases.
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DOI: 10.1109/PERCOMW.2015.7134065
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<front><div type="abstract" xml:lang="en">Crowdsensing has been used quite regularly in recent years to study smartphone usage. However context information associated with smartphone usage is mostly of the type geo-localisation, user mobility, temporal behavior etc. Furthermore most studies are not sufficiently user-centric i.e. don't consider the perception or cognitive aspects of the user. In this paper we collect data about social context and user perception via in-app and on-line questionnaires and show that when these are combined with crowdsensed data can help improve both sensing and survey and can be applied to interesting cases.</div>
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<abstract xml:lang="en">Crowdsensing has been used quite regularly in recent years to study smartphone usage. However context information associated with smartphone usage is mostly of the type geo-localisation, user mobility, temporal behavior etc. Furthermore most studies are not sufficiently user-centric i.e. don't consider the perception or cognitive aspects of the user. In this paper we collect data about social context and user perception via in-app and on-line questionnaires and show that when these are combined with crowdsensed data can help improve both sensing and survey and can be applied to interesting cases.</abstract>
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