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Use este identificador para citar o ir al link de este elemento: http://hdl.handle.net/1843/49047
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Campo DCValorIdioma
dc.creatorMinhui Xuept_BR
dc.creatorGabriel Magno de Oliveira Silvapt_BR
dc.creatorEvandro Landulfo Teixeira Paradela Cunhapt_BR
dc.creatorVirgilio Augusto Fernandes Almeidapt_BR
dc.creatorKeith W. Rosspt_BR
dc.date.accessioned2023-01-20T20:27:57Z-
dc.date.available2023-01-20T20:27:57Z-
dc.date.issued2016-
dc.citation.volume2016pt_BR
dc.citation.issue4pt_BR
dc.citation.spage389pt_BR
dc.citation.epage402pt_BR
dc.identifier.doihttps://doi.org/10.1515/popets-2016-0046pt_BR
dc.identifier.issn2299-0984pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/49047-
dc.description.resumoDue to the recent “Right to be Forgotten” (RTBF) ruling, for queries about an individual, Google and other search engines now delist links to web pages that contain “inadequate, irrelevant or no longer relevant, or excessive” information about that individual. In this paper we take a datadriven approach to study the RTBF in the traditional media outlets, its consequences, and its susceptibility to inference attacks. First, we do a content analysis on 283 known delisted UK media pages, using both manual investigation and Latent Dirichlet Allocation (LDA). We find that the strongest topic themes are violent crime, road accidents, drugs, murder, prostitution, financial misconduct, and sexual assault. Informed by this content analysis, we then show how a third party can discover delisted URLs along with the requesters’ names, thereby putting the efficacy of the RTBF for delisted media links in question. As a proof of concept, we perform an experiment that discovers two previously-unknown delisted URLs and their corresponding requesters. We also determine 80 requesters for the 283 known delisted media pages, and examine whether they suffer from the “Streisand effect,” a phenomenon whereby an attempt to hide a piece of information has the unintended consequence of publicizing the information more widely. To measure the presence (or lack of presence) of a Streisand effect, we develop novel metrics and methodology based on Google Trends and Twitter data. Finally, we carry out a demographic analysis of the 80 known requesters. We hope the results and observations in this paper can inform lawmakers as they refine RTBF laws in the future.pt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentFALE - FACULDADE DE LETRASpt_BR
dc.publisher.departmentICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃOpt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofProceedings on Privacy Enhancing Technologiespt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectPrivacypt_BR
dc.subjectRight to be forgottenpt_BR
dc.subjectStreisand effectpt_BR
dc.subjectLatent Dirichlet Allocationpt_BR
dc.subject.otherDireito a privacidadept_BR
dc.titleThe right to be forgotten in the media: a data-driven studypt_BR
dc.title.alternativeO direito ao esquecimento na mídia: um estudo baseado em dadospt_BR
dc.typeArtigo de Periódicopt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-7274-3116pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-6452-0361pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-3429-6490pt_BR
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