Predicting the Amount of GDPR Fines

dc.contributor.authorRuohonen Jukka
dc.contributor.authorHjerppe Kalle
dc.contributor.organizationfi=ohjelmistotekniikka|en=Software Engineering|
dc.contributor.organization-code1.2.246.10.2458963.20.71310837563
dc.contributor.organization-code2610302
dc.converis.publication-id53624472
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/53624472
dc.date.accessioned2022-10-28T13:32:17Z
dc.date.available2022-10-28T13:32:17Z
dc.description.abstract<p>Abstract. The General Data Protection Regulation (GDPR) was enforced in 2018. After this enforcement, many fines have already been imposed by national data protection authorities in the European Union (EU). This paper examines the individual GDPR articles referenced in the enforcement decisions, as well as predicts the amount of enforcement fines with available meta-data and text mining features extracted from the enforcement decision documents. According to the results, articles related to the general principles, lawfulness, and information security have been the most frequently referenced ones. Although the amount of fines imposed vary across the articles referenced, these three particular articles do not stand out. Furthermore, good predictions are attainable even with simple machine learning techniques for regression analysis. Basic meta-data (such as the articles referenced and the country of origin) yields slightly better performance compared to the text mining features. </p><p>Keywords: Text mining · Legal mining · Data protection · Law enforcement <br /></p>
dc.format.pagerange14
dc.format.pagerange3
dc.identifier.issn1613-0073
dc.identifier.jour-issn1613-0073
dc.identifier.olddbid182770
dc.identifier.oldhandle10024/165864
dc.identifier.urihttps://www.utupub.fi/handle/11111/40093
dc.identifier.urlhttp://ceur-ws.org/Vol-2690/COUrT-paper1.pdf
dc.identifier.urnURN:NBN:fi-fe2021042827544
dc.language.isoen
dc.okm.affiliatedauthorRuohonen, Jukka
dc.okm.affiliatedauthorHjerppe, Kalle
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryGermanyen_GB
dc.publisher.countrySaksafi_FI
dc.publisher.country-codeDE
dc.relation.conferenceCOUrT - CAiSE for Legal Documents
dc.relation.ispartofjournalCEUR Workshop Proceedings
dc.relation.ispartofseriesCEUR Workshop Proceedings
dc.relation.volume2690
dc.source.identifierhttps://www.utupub.fi/handle/10024/165864
dc.titlePredicting the Amount of GDPR Fines
dc.title.bookProceedings of the First International Workshop “CAiSE for Legal Documents” (COUrT 2020)
dc.year.issued2020

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