Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint

Bauer M, Heimstädt M, Franzreb C, Schimmler S (2023)
Big Data & Society 10(2): 20539517231180575.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
OA 1.58 MB
Autor*in
Bauer, Mareike; Heimstädt, MaximilianUniBi; Franzreb, Carlos; Schimmler, Sonja
Abstract / Bemerkung
Many scientists share preprints on social media platforms to gain attention from academic peers, policy-makers, and journalists. In this study we shed light on an unintended but highly consequential effect of sharing preprints: Their contribution to conspiracy theories. Although the scientific community might quickly dismiss a preprint as insubstantial and 'clickbaity', its uncertain epistemic status nevertheless allows conspiracy theorists to mobilize the text as scientific support for their own narratives. To better understand the epistemic politics of preprints on social media platforms, we studied the case of a biomedical preprint, which was shared widely and discussed controversially on Twitter in the wake of the coronavirus disease 2019 pandemic. Using a combination of social network analysis and qualitative content analysis, we compared the structures of engagement with the preprint and the discursive practices of scientists and conspiracy theorists. We found that despite substantial engagement, scientists were unable to dampen the conspiracy theorists' enthusiasm for the preprint. We further found that members from both groups not only tried to reduce the preprint's epistemic uncertainty but sometimes deliberately maintained it. The maintenance of epistemic uncertainty helped conspiracy theorists to reinforce their group's identity as skeptics and allowed scientists to express concerns with the state of their profession. Our study contributes to research on the intricate relations between scientific knowledge and conspiracy theories online, as well as the role of social media platforms for new genres of scholarly communication.
Stichworte
Preprint; scholarly communication; conspiracy theorists; twitter; social; network analysis; social media
Erscheinungsjahr
2023
Zeitschriftentitel
Big Data & Society
Band
10
Ausgabe
2
Art.-Nr.
20539517231180575
eISSN
2053-9517
Page URI
https://pub.uni-bielefeld.de/record/2983427

Zitieren

Bauer M, Heimstädt M, Franzreb C, Schimmler S. Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint. Big Data & Society . 2023;10(2): 20539517231180575.
Bauer, M., Heimstädt, M., Franzreb, C., & Schimmler, S. (2023). Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint. Big Data & Society , 10(2), 20539517231180575. https://doi.org/10.1177/20539517231180575
Bauer, Mareike, Heimstädt, Maximilian, Franzreb, Carlos, and Schimmler, Sonja. 2023. “Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint”. Big Data & Society 10 (2): 20539517231180575.
Bauer, M., Heimstädt, M., Franzreb, C., and Schimmler, S. (2023). Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint. Big Data & Society 10:20539517231180575.
Bauer, M., et al., 2023. Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint. Big Data & Society , 10(2): 20539517231180575.
M. Bauer, et al., “Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint”, Big Data & Society , vol. 10, 2023, : 20539517231180575.
Bauer, M., Heimstädt, M., Franzreb, C., Schimmler, S.: Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint. Big Data & Society . 10, : 20539517231180575 (2023).
Bauer, Mareike, Heimstädt, Maximilian, Franzreb, Carlos, and Schimmler, Sonja. “Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint”. Big Data & Society 10.2 (2023): 20539517231180575.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International Public License (CC BY-SA 4.0):
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2024-02-08T10:44:20Z
MD5 Prüfsumme
928a8c0cd7721f7d88c45ddb20081110


Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Suchen in

Google Scholar