The COVID-19 Pandemic, Twitter, and the Archetype of “Country Savior” in the Ukrainian Case Cover Image

The COVID-19 Pandemic, Twitter, and the Archetype of “Country Savior” in the Ukrainian Case
The COVID-19 Pandemic, Twitter, and the Archetype of “Country Savior” in the Ukrainian Case

Author(s): Nataliia Oleksandrivna Steblyna, Iryna Matsyshyna, Olena Skalatska
Subject(s): Politics / Political Sciences, Communication studies, Politics and communication, Politics and society, Health and medicine and law
Published by: Editura Universităţii din Bucureşti
Keywords: Archetype; vaccination; discourse; manipulation; Twitter;

Summary/Abstract: The COVID-19 pandemic has attracted the attention of social scientists to the study of the role and influence of archetypes on public opinion. Ukrainian politicians have been informing citizens on social networks about the fight against the pandemic. It was presented as a feat, the salvation of not only the nation, but also of the world. Politicians have been independently constructing an image of the hero who helps to create a vaccine or arrange its supply and save the country’s population. To establish the archetype of the hero through the discourse of vaccination, this article analyzes the strategies of constructing the archetype of the “country savior,” using the Greimas actantial model. As a result, the actantial categories were discovered by using computer semantic analysis of tweets. The authors found that politicians used the archetypes of the savior- industrialist (Viktor Medvedchuk), savior-inspirer (Volodymyr Zelenskyy), and savior-patron (Petro Poroshenko). A method for measuring negativism and its intensity in the messages of politicians was also proposed, and it was found that the government officials perceive the situation in a more positive way, while the opposition mostly negatively. It was also found that the amount of negativism and its intensity can be interpreted through the actantial models.

  • Issue Year: 22/2022
  • Issue No: 1
  • Page Range: 67-95
  • Page Count: 29
  • Language: English
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