Publikationsdatenbank

Social cohesion during the stay-at-home phase of the first wave of the COVID-19 pandemic on Polish-speaking twitter (2021)

Art

Buchbeitrag

Autoren

Jarynowski, Andrzej (WE 16)

Semenov, Alexander

Wójta-Kempa, Monika

Belik, Vitaly (WE 16)

Quelle

Computational data and social networks : 10th international conference, CSoNet 2021 : virtual event, November 15–17, 2021 : proceedings — David Mohaisen, Ruoming Jin (Hrsg.)

1. Auflage

Cham: Springer, 2021. Lecture notes in computer science ; 13116 — S. 361–370

ISBN: 978-3-030-91434-9

Sprache

Englisch

Verweise

URL (Volltext): https://link.springer.com/chapter/10.1007%2F978-3-030-91434-9_31

DOI: 10.1007/978-3-030-91434-9_31

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

Königsweg 67
14163 Berlin
+49 30 838 56034
epi@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Catastrophic and urgent events, such as the COVID-19 pandemic, are known not only to polarize societies and induce selfish, individualistic behavior, but might also motivate altruistic behavior. We have analyzed COVID-19 perception using data collected from the Polish-language Internet from 15.01-30.06.2020, equaling 930,319 tweets. Deploying methods of computational social science and digital epidemiology, we aim to understand mechanisms of social consolidation and depolarization (measured by network modularity and sentiment) during the so-called “stay-at-home phase” of the COVID-19 pandemic. Mauss’ theory of interaction or exchange of gifts, the theory of social capital, as well as Kaniasty’s theory of mobilization and deterioration serve as a background for reflection on the Polish example during the first epidemic wave. Our study highlights the potential of social support and caretaking to reduce affective and behavioral polarization in social media