DC FieldValueLanguage
dc.contributor.authorAnagnostopoulos, Theodoros-
dc.contributor.authorHosio, Simo-
dc.contributor.authorFerreira, Denzil-
dc.contributor.authorVan Berkel, Niels-
dc.contributor.authorLuo, Chu-
dc.contributor.authorKostakos, Vassilis-
dc.contributor.authorGoncalves, Jorge-
dc.date.accessioned2024-07-09T12:36:18Z-
dc.date.available2024-07-09T12:36:18Z-
dc.date.issued2016-05-07-
dc.identifierscopus-84991436016-
dc.identifier.isbn978-1-4503-3362-7-
dc.identifier.other84991436016-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2697-
dc.description.abstractResearchers who analyse smartphone usage logs often make the assumption that users who lock and unlock their phone for brief periods of time (e.g., less than a minute) are continuing the same "session" of interaction. However, this assumption is not empirically validated, and in fact different studies apply different arbitrary thresholds in their analysis. To validate this assumption, we conducted a field study where we collected user-labelled activity data through ESM and sensor logging. Our results indicate that for the majority of instances where users return to their smartphone, i.e., unlock their device, they in fact begin a new session as opposed to continuing a previous one. Our findings suggest that the commonly used approach of ignoring brief standby periods is not reliable, but optimisation is possible. We therefore propose various metrics related to usage sessions and evaluate various machine learning approaches to classify gaps in usage.en_US
dc.language.isoenen_US
dc.relation.ispartofCHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systemsen_US
dc.subjectClassification modelsen_US
dc.subjectESMen_US
dc.subjectHuman behaviouren_US
dc.subjectMachine learningen_US
dc.subjectMobile devicesen_US
dc.subjectPhone usageen_US
dc.subjectSessionen_US
dc.titleA systematic assessment of smartphone usage gapsen_US
dc.typeConference Paperen_US
dc.relation.conferenceCHI '16: CHI Conference on Human Factors in Computing Systems, 7-12 May 2016, San Jose California, USAen_US
dc.identifier.doi10.1145/2858036.2858348en_US
dc.identifier.scopus2-s2.0-84991436016-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.identifier.spage4711en_US
dc.identifier.epage4721en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusnot verifieden_US
item.openairetypeConference Paper-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-5587-2848-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου
CORE Recommender
Show simple item record

SCOPUSTM   
Citations

51
checked on Sep 6, 2024

Page view(s)

17
checked on Sep 11, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.