Publikationsdatenbank

Protest perspective against COVID-19 risk mitigation strategies on the German internet (2020)

Art

Buchbeitrag

Autoren

Jarynowski, Andrzej (WE 16)

Semenov, Alexander

Belik, Vitaly (WE 16)

Quelle

Computational data and social networks : 9th International Conference, CSoNet 2020, Dallas, TX, USA, December 11–13, 2020, proceedings — Sriram Chellappan, Kim-Kwang Raymond Choo, NhatHai Phan (Hrsg.)

1st edition 2020 Auflage

Cham: Springer International Publishing, 2020. Lecture notes in computer science ; 12575 — S. 524–535

ISBN: 978-3-030-66046-8

Sprache

Englisch

Verweise

URL (Volltext): https://link.springer.com/chapter/10.1007%2F978-3-030-66046-8_43

DOI: 10.1007/978-3-030-66046-8_43

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

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

Abstract / Zusammenfassung

The aim of this study is to quantitatively assess perception of protests around COVID-19 in Germany from the late July till the end of August 2020 in the Internet media by infodemiological approach. To this end we investigate Google searches, Twitter and Telegram posts, and selection of news articles via EventRegistry. We focus on narratives around Berlin Demonstrations on August 1st and August 29th, 2020. Using media intelligence we spot trends, analyze relevant topics over a longer time span and create sociolinguistic landscapes targeting Querdenken and QAnon movements and other actors such as AfD, SPD, and Green political parties and Antifa. Although the dominant actors of the protest are on the far-right political spectrum, we demonstrate (based on network analysis) that left-wing activists could both sympathize with (e.g. some liberal greens) and oppose (e.g. Antifa) the protest. Although we observe a constant interest in the protest movements in traditional media, their popularity on social media is growing (for Querdenken faster than for QAnon). The revealed insights shed light on social dynamics in the context of such major disruptive events as COVID-19 pandemic and could serve as a basis for optimization of risk awareness campaigns by the authorities.