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Structuring and Exploring User Behavioral Patterns in Social Media Traces

dc.contributor.authorHerder, Eelco
dc.contributor.authorRoßner, Daniel
dc.contributor.authorAtzenbeck, Claus
dc.contributor.editorHansen, Christian
dc.contributor.editorNürnberger, Andreas
dc.contributor.editorPreim, Bernhard
dc.date.accessioned2020-08-18T15:19:49Z
dc.date.available2020-08-18T15:19:49Z
dc.date.issued2020
dc.description.abstractUser behavior and the resulting behavioral data forms the basis of personalized feeds, recommendations and advertisements in social networks such as Facebook. These platforms are now required to provide users with their personal data. However, these dumps with chronological data in different files do not provide users insight in overarching themes and connections in their online behavior. In this paper, we discuss the development and preliminary evaluation of an exploratory interface for visual data exploration. First insights include that the less obvious, more associative and obscure connections are more interesting and relevant to the user than very close semantic or temporal connections.en
dc.identifier.doi10.18420/muc2020-ws111-343
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/33511
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2020 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.subjectspatial hypertext
dc.subjectsocial networks
dc.subjectuser profiles
dc.subjectGDPR
dc.subjectdata exploration
dc.subjecttransparency
dc.titleStructuring and Exploring User Behavioral Patterns in Social Media Tracesen
dc.typeText/Workshop Paper
gi.citation.publisherPlaceBonn
gi.conference.date6.-9. September 2020
gi.conference.locationMagdeburg
gi.conference.sessiontitleMCI-WS02: UCAI 2020: Workshop on User-Centered Artificial Intelligence
gi.document.qualitydigidoc

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