Analysis of the influence of political polarization in the vaccination stance: the Brazilian COVID-19 scenario
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Abstract (arXiv)
The outbreak of COVID-19 had a huge global impact, and non-scientific beliefs and political polarization have significantly influenced the population's behavior. In this context, COVID vaccines were made available in an unprecedented time, but a high level of hesitance has been observed that can undermine community immunization. Traditionally, anti-vaccination attitudes are more related to conspiratorial thinking rather than political bias. In Brazil, a country with an exemplar tradition in large-scale vaccination programs, all COVID-related topics have also been discussed under a strong political bias. In this paper, we use a multidimensional analysis framework to understand if anti/pro-vaccination stances expressed by Brazilians in social media are influenced by political polarization. The analysis framework incorporates techniques to automatically infer from users their political orientation, topic modeling to discover their concerns, network analysis to characterize their social behavior, and the characterization of information sources and external influence. Our main findings confirm that anti/pro stances are biased by political polarization, right and left, respectively. While a significant proportion of pro-vaxxers display haste for an immunization program and criticize the government's actions, the anti-vaxxers distrust a vaccine developed in a record time. Anti-vaccination stance is also related to prejudice against China (anti-sinovaxxers), revealing conspiratorial theories related to communism. All groups display an "echo chamber behavior, revealing they are not open to distinct views.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Oct 2021.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 2.
5 papers.
- 2022Using Twitter Data to Understand Public Perceptions of Approved versus Off-label Use for COVID-19-related Medicationscited by 8
- 2024Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Mediacited by 7
- 2023Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarization on Social Media Discoursecited by 2
- 2023Exploring the evolution of research topics during the COVID-19 pandemiccited by 1
- 2024Capturing research literature attitude towards Sustainable Development Goals: an LLM-based topic modeling approachcited by 1
- 2024Capturing research literature attitude towards Sustainable Development Goals: an LLM-based topic modeling approach5 Nov 2024
- 2024Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media6 Mar 2024
- 2023Exploring the evolution of research topics during the COVID-19 pandemic5 Oct 2023
- 2023Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarization on Social Media Discourse20 Jan 2023
- 2022Using Twitter Data to Understand Public Perceptions of Approved versus Off-label Use for COVID-19-related Medications29 Jun 2022