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dc.contributor.authorPedersen, Marius Alexander
dc.contributor.authorGuribye, Frode
dc.contributor.authorSlavkovik, Marija
dc.date.accessioned2023-09-11T12:24:37Z
dc.date.available2023-09-11T12:24:37Z
dc.date.created2023-09-03T09:42:24Z
dc.date.issued2023
dc.identifier.isbn0000000000
dc.identifier.urihttps://hdl.handle.net/11250/3088667
dc.description.abstractWe study how to automatically classify different types of manipulative interface design pattern for Content Management Platforms (CMPs), also known as a cookie consents. Our approach uses a scraper to extract different features of CMPs. We then classify the CMP, based on these features, into one of five patterns defined specifically for CMPs. We evaluate our automatic "detector" using four different statistical measures. We also consider factors that cause misclassifications and discuss how to potentially avoid them.en_US
dc.language.isoengen_US
dc.relation.ispartofProceedings of the 5th Symposium of the Norwegian AI Society
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAutomatic Detection of Manipulative Consent Management Platforms and the Journey into the Patterns of Darknessen_US
dc.typeChapteren_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.source.articlenumber6en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
dc.identifier.cristin2171831
dc.identifier.citationNAIS 2023: The 2023 symposium of the Norwegian AI Society. 2023, 3431, 6.en_US
dc.source.volume3431en_US


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal