The spread of fake news: a case study of the presidential elections of 2018 in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | https://hdl.handle.net/10438/30800 |
Resumo: | As fake news becomes more pervasive with the increasing adoption of digital platforms, understanding how disinformation spread and the factors that contribute to its continuation has become crucial, given the detrimental effects for democracies. This study investigates the spread of fake news during the Presidential Elections of 2018 in Brazil and how distinct social media and websites are used as distribution platforms and sources of disinformation. For such, a pre-existing data set of 346 fake news stories collected during the elections served as a starting point. Initially, through a reverse search process, the main websites responsible for disseminating disinformation were mapped. These sources were then analysed in terms of traffic and partisanship. Beyond a prevalence of right-wing fake news sources, a high concentration of web traffic was found. Five websites were responsible for almost 80% of all pageviews (or impressions) from all the 58 identified fake news sources. Furthermore, in order to investigate the circulation of disinformation on Facebook, Twitter and WhatsApp, the data set was filtered into the 58 most relevant unique fake news stories, which were later classified by political bias, engagement (number of shares), and segregated in four narratives. Firstly, it was found that all the analysed social media served as relevant distribution platforms for fake news, once 32 out of the 58 fake news stories circulated in all of them. Yet, Facebook was found to be more relevant than Twitter for that purpose. Secondly, the four major narratives that shaped the fake news stories were mostly related to an intense polarization and declining rates of trust in public institutions and media vehicles. Among these, fake news related to anti-left/anti-workers were predominant. Similarly to the first analysis, partisanship was noticeable during the spread of disinformation, as there were ten times more pro-Bolsonaro (or anti-Haddad) fake news stories than the polar opposite. Finally, the findings indicate that, while Facebook and Twitter were relevant distribution platforms, WhatsApp had a major impact on closed groups due to the reinforced cognitive effects and externalities that corroborate to the susceptibility and spread of fake news on social media. |
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spelling |
Hattori, GuilhermeEscolas::EAESPLanka, SanjayFerreira, Tiago AndréMukhi, Umesh Dilip Kumar2021-07-02T18:34:01Z2021-07-02T18:34:01Z2021-03-12https://hdl.handle.net/10438/30800As fake news becomes more pervasive with the increasing adoption of digital platforms, understanding how disinformation spread and the factors that contribute to its continuation has become crucial, given the detrimental effects for democracies. This study investigates the spread of fake news during the Presidential Elections of 2018 in Brazil and how distinct social media and websites are used as distribution platforms and sources of disinformation. For such, a pre-existing data set of 346 fake news stories collected during the elections served as a starting point. Initially, through a reverse search process, the main websites responsible for disseminating disinformation were mapped. These sources were then analysed in terms of traffic and partisanship. Beyond a prevalence of right-wing fake news sources, a high concentration of web traffic was found. Five websites were responsible for almost 80% of all pageviews (or impressions) from all the 58 identified fake news sources. Furthermore, in order to investigate the circulation of disinformation on Facebook, Twitter and WhatsApp, the data set was filtered into the 58 most relevant unique fake news stories, which were later classified by political bias, engagement (number of shares), and segregated in four narratives. Firstly, it was found that all the analysed social media served as relevant distribution platforms for fake news, once 32 out of the 58 fake news stories circulated in all of them. Yet, Facebook was found to be more relevant than Twitter for that purpose. Secondly, the four major narratives that shaped the fake news stories were mostly related to an intense polarization and declining rates of trust in public institutions and media vehicles. Among these, fake news related to anti-left/anti-workers were predominant. Similarly to the first analysis, partisanship was noticeable during the spread of disinformation, as there were ten times more pro-Bolsonaro (or anti-Haddad) fake news stories than the polar opposite. Finally, the findings indicate that, while Facebook and Twitter were relevant distribution platforms, WhatsApp had a major impact on closed groups due to the reinforced cognitive effects and externalities that corroborate to the susceptibility and spread of fake news on social media.A crescente adoção das plataformas digitais tem impulsionado a ascensão das fake news, tornando, portanto, essencial que se entenda como a desinformação se espalha e quais os fatores que contribuem para que o fenômeno continue, dadas as implicações à democracia. Este estudo investiga a disseminação de fake News durante as eleições presidenciais de 2018 no Brazil e como distintas redes sociais e websites foram usados como fontes e plataformas de distribuição de desinformação. Para isso, um banco de dados de 346 fake news, coletadas em um estudo durante as eleições, serviu como ponto de partida. Inicialmente, por meio de uma busca reversa, os principais sites responsáveis por espalhar fake news foram mapeados. Essas fontes foram então analisadas em termos de tráfego gerado e viés político. Além da prevalência de fontes de direita, o estudo encontrou uma alta concentração de tráfego. Cinco websites foram responsáveis por quase 80% de todas as impressões (pageviews) dentre as 58 fontes de desinformação mapeadas. Posteriormente, para que se investigasse a circulação de desinformação nas redes Facebook, Twitter e WhatsApp, o banco de dados foi filtrado a 58 fake news únicas mais relevantes, que foram em sequência classificadas de acordo com viés político, engajamento (compartilhamentos), e segregadas em quatro narrativas. Primeiramente, foi constatado que todas as mídias sociais analisadas serviram como relevantes plataformas de distribuição de fake news, uma vez que 32 das 58 histórias circularam em todas elas. No entanto, o Facebook mostra-se mais relevante que o Twitter para este fim. Em seguida, constatou-se que as quatro narrativas que moldam as principais fake news estavam relacionadas à intensa polarização, ao declínio da confiança nas instituições públicas e nos veículos midiáticos mais tradicionais. Similarmente à primeira análise, o nota-se o característico viés político na disseminação de desinformação, uma vez que havia dez vezes mais fake news pro-Bolsonaro (ou anti-Haddad) do que o oposto. Por fim, os resultados também indicam que, enquanto o Facebook e o Twitter foram importante plataformas para a distribuição de fake news, o WhatsApp teve um impacto mais significativo em grupos fechados, uma vez que reforça os efeitos cognitivos e externalidades que corroboram para a suscetibilidade e ao compartilhamento de fake news nas redes sociais.engFake newsDisinformationPresidential electionsSocial mediaSourcesDistribution platformsSpreadSusceptibilityPartisanshipDesinformaçãoEleições presidenciaisMídias sociaisFontesPlataformas de distribuiçãoDisseminaçãoSuscetibilidadePartidarismoAdministração de empresasFake newsDesinformaçãoPresidentes - Brasil - EleiçõesEleições - Brasil - 2018Redes sociais on-lineThe spread of fake news: a case study of the presidential elections of 2018 in Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação 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dc.title.eng.fl_str_mv |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
title |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
spellingShingle |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil Hattori, Guilherme Fake news Disinformation Presidential elections Social media Sources Distribution platforms Spread Susceptibility Partisanship Desinformação Eleições presidenciais Mídias sociais Fontes Plataformas de distribuição Disseminação Suscetibilidade Partidarismo Administração de empresas Fake news Desinformação Presidentes - Brasil - Eleições Eleições - Brasil - 2018 Redes sociais on-line |
title_short |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
title_full |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
title_fullStr |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
title_full_unstemmed |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
title_sort |
The spread of fake news: a case study of the presidential elections of 2018 in Brazil |
author |
Hattori, Guilherme |
author_facet |
Hattori, Guilherme |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EAESP |
dc.contributor.member.none.fl_str_mv |
Lanka, Sanjay Ferreira, Tiago André |
dc.contributor.author.fl_str_mv |
Hattori, Guilherme |
dc.contributor.advisor1.fl_str_mv |
Mukhi, Umesh Dilip Kumar |
contributor_str_mv |
Mukhi, Umesh Dilip Kumar |
dc.subject.eng.fl_str_mv |
Fake news Disinformation Presidential elections Social media Sources Distribution platforms Spread Susceptibility Partisanship |
topic |
Fake news Disinformation Presidential elections Social media Sources Distribution platforms Spread Susceptibility Partisanship Desinformação Eleições presidenciais Mídias sociais Fontes Plataformas de distribuição Disseminação Suscetibilidade Partidarismo Administração de empresas Fake news Desinformação Presidentes - Brasil - Eleições Eleições - Brasil - 2018 Redes sociais on-line |
dc.subject.por.fl_str_mv |
Desinformação Eleições presidenciais Mídias sociais Fontes Plataformas de distribuição Disseminação Suscetibilidade Partidarismo |
dc.subject.area.por.fl_str_mv |
Administração de empresas |
dc.subject.bibliodata.por.fl_str_mv |
Fake news Desinformação Presidentes - Brasil - Eleições Eleições - Brasil - 2018 Redes sociais on-line |
description |
As fake news becomes more pervasive with the increasing adoption of digital platforms, understanding how disinformation spread and the factors that contribute to its continuation has become crucial, given the detrimental effects for democracies. This study investigates the spread of fake news during the Presidential Elections of 2018 in Brazil and how distinct social media and websites are used as distribution platforms and sources of disinformation. For such, a pre-existing data set of 346 fake news stories collected during the elections served as a starting point. Initially, through a reverse search process, the main websites responsible for disseminating disinformation were mapped. These sources were then analysed in terms of traffic and partisanship. Beyond a prevalence of right-wing fake news sources, a high concentration of web traffic was found. Five websites were responsible for almost 80% of all pageviews (or impressions) from all the 58 identified fake news sources. Furthermore, in order to investigate the circulation of disinformation on Facebook, Twitter and WhatsApp, the data set was filtered into the 58 most relevant unique fake news stories, which were later classified by political bias, engagement (number of shares), and segregated in four narratives. Firstly, it was found that all the analysed social media served as relevant distribution platforms for fake news, once 32 out of the 58 fake news stories circulated in all of them. Yet, Facebook was found to be more relevant than Twitter for that purpose. Secondly, the four major narratives that shaped the fake news stories were mostly related to an intense polarization and declining rates of trust in public institutions and media vehicles. Among these, fake news related to anti-left/anti-workers were predominant. Similarly to the first analysis, partisanship was noticeable during the spread of disinformation, as there were ten times more pro-Bolsonaro (or anti-Haddad) fake news stories than the polar opposite. Finally, the findings indicate that, while Facebook and Twitter were relevant distribution platforms, WhatsApp had a major impact on closed groups due to the reinforced cognitive effects and externalities that corroborate to the susceptibility and spread of fake news on social media. |
publishDate |
2021 |
dc.date.accessioned.fl_str_mv |
2021-07-02T18:34:01Z |
dc.date.available.fl_str_mv |
2021-07-02T18:34:01Z |
dc.date.issued.fl_str_mv |
2021-03-12 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10438/30800 |
url |
https://hdl.handle.net/10438/30800 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do FGV (FGV Repositório Digital) instname:Fundação Getulio Vargas (FGV) instacron:FGV |
instname_str |
Fundação Getulio Vargas (FGV) |
instacron_str |
FGV |
institution |
FGV |
reponame_str |
Repositório Institucional do FGV (FGV Repositório Digital) |
collection |
Repositório Institucional do FGV (FGV Repositório Digital) |
bitstream.url.fl_str_mv |
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Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV) |
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1813797760079495168 |