The right to be forgotten in the media: a data-driven study
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFMG |
Texto Completo: | https://doi.org/10.1515/popets-2016-0046 http://hdl.handle.net/1843/49047 https://orcid.org/0000-0002-7274-3116 https://orcid.org/0000-0001-6452-0361 https://orcid.org/0000-0002-3429-6490 |
Resumo: | Due 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. |
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2023-01-20T20:27:57Z2023-01-20T20:27:57Z201620164389402https://doi.org/10.1515/popets-2016-00462299-0984http://hdl.handle.net/1843/49047https://orcid.org/0000-0002-7274-3116https://orcid.org/0000-0001-6452-0361https://orcid.org/0000-0002-3429-6490Due 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.engUniversidade Federal de Minas GeraisUFMGBrasilFALE - FACULDADE DE LETRASICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃOProceedings on Privacy Enhancing TechnologiesDireito a privacidadePrivacyRight to be forgottenStreisand effectLatent Dirichlet AllocationThe right to be forgotten in the media: a data-driven studyO direito ao esquecimento na mídia: um estudo baseado em dadosinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleMinhui XueGabriel Magno de Oliveira SilvaEvandro Landulfo Teixeira Paradela CunhaVirgilio Augusto Fernandes AlmeidaKeith W. Rossapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALThe Right to be Forgotten in the Media A Data-Driven Study.pdfThe Right to be Forgotten in the Media A Data-Driven Study.pdfapplication/pdf655154https://repositorio.ufmg.br/bitstream/1843/49047/2/The%20Right%20to%20be%20Forgotten%20in%20the%20Media%20A%20Data-Driven%20Study.pdfb4b333548f499825c207da321ea799aaMD52LICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/49047/1/License.txtfa505098d172de0bc8864fc1287ffe22MD511843/490472023-01-20 17:27:58.252oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-01-20T20:27:58Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.pt_BR.fl_str_mv |
The right to be forgotten in the media: a data-driven study |
dc.title.alternative.pt_BR.fl_str_mv |
O direito ao esquecimento na mídia: um estudo baseado em dados |
title |
The right to be forgotten in the media: a data-driven study |
spellingShingle |
The right to be forgotten in the media: a data-driven study Minhui Xue Privacy Right to be forgotten Streisand effect Latent Dirichlet Allocation Direito a privacidade |
title_short |
The right to be forgotten in the media: a data-driven study |
title_full |
The right to be forgotten in the media: a data-driven study |
title_fullStr |
The right to be forgotten in the media: a data-driven study |
title_full_unstemmed |
The right to be forgotten in the media: a data-driven study |
title_sort |
The right to be forgotten in the media: a data-driven study |
author |
Minhui Xue |
author_facet |
Minhui Xue Gabriel Magno de Oliveira Silva Evandro Landulfo Teixeira Paradela Cunha Virgilio Augusto Fernandes Almeida Keith W. Ross |
author_role |
author |
author2 |
Gabriel Magno de Oliveira Silva Evandro Landulfo Teixeira Paradela Cunha Virgilio Augusto Fernandes Almeida Keith W. Ross |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Minhui Xue Gabriel Magno de Oliveira Silva Evandro Landulfo Teixeira Paradela Cunha Virgilio Augusto Fernandes Almeida Keith W. Ross |
dc.subject.por.fl_str_mv |
Privacy Right to be forgotten Streisand effect Latent Dirichlet Allocation |
topic |
Privacy Right to be forgotten Streisand effect Latent Dirichlet Allocation Direito a privacidade |
dc.subject.other.pt_BR.fl_str_mv |
Direito a privacidade |
description |
Due 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. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016 |
dc.date.accessioned.fl_str_mv |
2023-01-20T20:27:57Z |
dc.date.available.fl_str_mv |
2023-01-20T20:27:57Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1843/49047 |
dc.identifier.doi.pt_BR.fl_str_mv |
https://doi.org/10.1515/popets-2016-0046 |
dc.identifier.issn.pt_BR.fl_str_mv |
2299-0984 |
dc.identifier.orcid.pt_BR.fl_str_mv |
https://orcid.org/0000-0002-7274-3116 https://orcid.org/0000-0001-6452-0361 https://orcid.org/0000-0002-3429-6490 |
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https://doi.org/10.1515/popets-2016-0046 http://hdl.handle.net/1843/49047 https://orcid.org/0000-0002-7274-3116 https://orcid.org/0000-0001-6452-0361 https://orcid.org/0000-0002-3429-6490 |
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2299-0984 |
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eng |
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eng |
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Proceedings on Privacy Enhancing Technologies |
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openAccess |
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Universidade Federal de Minas Gerais |
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UFMG |
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Brasil |
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FALE - FACULDADE DE LETRAS ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO |
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Universidade Federal de Minas Gerais |
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