Fake news e polarização política no Brasil: o antibolsonarismo no twitter desde a pandemia Covid-19 até às eleições presidenciais de 2022

Translated title of the contribution: Fake news and political polarization in Brazil: antibolsonarism on twitter from the Covid-19 pandemic until the 2022 presidential elections

A. Pereira

Research output: Contribution to conferencePaperpeer-review

Abstract

“Fake news” include a diverse mesh of false information, defamation and slander – disseminated in an organized and strategic way, or through organic networks (Zhuravskaya et al, 2020). This is a qualitative investigation, combining participant observation with data collected through a prolonged online ethnography, carried out between the Spring of 2020 (beginning of the pandemic crisis), through the CPI of Covid in the Brazilian Senate (April-October 2021), and until to Autumn of 2022 (Brazilian presidential elections). It was carried out through the social network Twitter, and data were analyzed by using NVivo 11. The results allow the analysis of the typical modus operandi of both Bolsonarism and anti-Bolsonarism, including the graphs shared by data analysts (Barciela and Malini, 2020-2022). They will be particularly relevant to European sociologists who are interested in the American influence on Brazilian politics and on the ways how new media influence and interact with political events.
Translated title of the contributionFake news and political polarization in Brazil: antibolsonarism on twitter from the Covid-19 pandemic until the 2022 presidential elections
Original languagePortuguese
Number of pages26
Publication statusPublished - 6 Apr 2023
EventXII Congresso Português de Sociologia - Faculdade de Economia da Universidade de Coimbra, Coimbra, Portugal
Duration: 4 Apr 20236 Apr 2023
https://eu-central-1.linodeobjects.com/evt4-media/documents/Programa_Com._APS_6Abr.pdf

Conference

ConferenceXII Congresso Português de Sociologia
Country/TerritoryPortugal
CityCoimbra
Period4/04/236/04/23
Internet address

Keywords

  • Fake news
  • Polarization
  • Twitter
  • Antibolsonarism

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