Show simple item record

dc.contributor.authorHINDMAN, Matthew
dc.date.accessioned2012-11-06T12:54:50Z
dc.date.available2012-11-06T12:54:50Z
dc.date.issued2012
dc.identifier.issn1028-3625
dc.identifier.urihttp://hdl.handle.net/1814/24296
dc.description.abstractOver the past two decades, much scholarship has theorized about how highly personalized news media might change the public sphere. But even as algorithmic content filtering has become widespread, social science research has lagged in understanding how such systems work, and how they have altered competitive dynamics between media outlets. Drawing on recent research into recommender systems, this paper examines the Netflix prize, as well as collaborative filtering algorithms deployed by Google and Yahoo. Content recommendation systems strongly advantage the very largest websites over small news outlets, with profound implications for the online news landscape.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesEUI RSCASen
dc.relation.ispartofseries2012/56en
dc.relation.ispartofseriesGlobal Governance Programme-29en
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectFuture of journalismen
dc.subjectonline public sphereen
dc.subjectrecommender systemsen
dc.subjectnews personalizationen
dc.subjectonline newsen
dc.subjectdigital journalismen
dc.titlePersonalization and the Future of Newsen
dc.typeWorking Paperen
eui.subscribe.skiptrue


Files in this item

Icon

This item appears in the following Collection(s)

Show simple item record