Quarenteners vs. Cloroquiners: a framework to analyze the effect of political polarization on social distance stances

  • Régis Ebeling Universidade Federal do Rio Grande do Sul
  • Carlos Córdova Sáenz Universidade Federal do Rio Grande do Sul
  • Jeferson Campos Nobre Universidade Federal do Rio Grande do Sul
  • Karin Becker Universidade Federal do Rio Grande do Sul


The worldwide COVID-19 pandemic has struck people’s lives overnight. With an alarming contagious rate and no effective treatments or vaccines, it has evoked all sorts of reactions. In this paper, we propose a framework to analyze how political polarization affects groups’ behavior with opposed stances, using the Brazilian COVID polarized scenario as a case study. Two Twitter groups represent the pro/against social isolation stances referred to as Chloroquiners and Quarenteners. The framework encompasses: a) techniques to automatically infer from users political orientation, b) topic modeling to discover the homogeneity of concerns expressed by each group; c) network analysis and community detection to characterize their behavior as a social network group and d) analysis of linguistic characteristics to identify psychological aspects. Our main findings confirm that Cloroquiners are right-wing partisans, whereas Quarenteners are more related to the left-wing. The political polarization of Chloroquiners and Quarenteners influence the arguments of economy and life, and support/opposition to the president. As a group, the network of Chloroquiners is more closed and connected, and Quarenteners have a more diverse political engagement. In terms of psychological aspects, polarized groups come together on cognitive issues and negative emotions.

Palavras-chave: political polarization, COVID-19, analysis framework, group behavior


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EBELING, Régis; SÁENZ, Carlos Córdova; NOBRE, Jeferson Campos; BECKER, Karin. Quarenteners vs. Cloroquiners: a framework to analyze the effect of political polarization on social distance stances. In: SYMPOSIUM ON KNOWLEDGE DISCOVERY, MINING AND LEARNING (KDMILE), 8. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 89-96. ISSN 2763-8944. DOI: https://doi.org/10.5753/kdmile.2020.11963.