Right-Wing Authoritarian Attitudes, Fast-Paced Decision-Making, and the Spread of Misinformation About COVID-19 Vaccines

ABSTRACT

Social media played a prominent role in the spread of vaccine-related fake news during the global COVID-19 crisis. Previous work has shown that both trait-related and situational factors influence the spread of fake news on social media. However, we have limited insight into how the specific contextual conditions that shape information processing on social media contribute to the proliferation of misinformation. In this article, we posit that people are more susceptible to spreading misinformation because they engage selectively, briefly, and heuristically with political news on social media. To test our argument, we rely on a pre-registered online experiment conducted in two Central and Eastern European (CEE) countries, Hungary and Romania. We designed this experiment to reflect the fast and impulsive decision-making that is characteristic of online behavior on social media platforms. The results support the idea that individuals’ tendency to disseminate fake news is amplified by conditions of fast-paced and impulsive decision-making. The effect is particularly pronounced among respondents with higher right-wing authoritarian attitudes. This suggests that the fast and intuition-reliant nature of decision-making on social media encourages the spread of such misinformation that is in line with individuals’ ideological beliefs, which could increase social polarization in societies.

KEYWORDS:

• COVID-19 misinformation
• fake news
• social media
• right-wing authoritarianism

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Supplementary Material

Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/10584609.2023.2291538

Data Availability Statement

All data and code are stored at Harvard Dataverse (DOI: https://doi.org/10.7910/DVN/YBEIYS). The repository also contains a Dockerfile that allows to run all analyses in a reproducible environment.

Open scholarship

This article has earned the Center for Open Science badges for Open Data, Open Materials and Preregistered. The data and materials are openly accessible at doi: 10.7910/DVN/YBEIYS

Notes

1. Misinformation can be understood as “fabricated information that mimics news media content in form but not in organizational process or intent” (Lazer et al., 2018). We use the term misinformation and fake news interchangeably throughout the manuscript.

2. A conspiracy theory can generally be defined as “an effort to explain some event or practice by reference to the machinations of powerful people, who attempt to conceal their role” (Sunstein & Vermeule, 2009).

3. Political extremism and authoritarianism is not exclusive to the right-wing. In light of previous findings related to COVID-19 conspiracy beliefs, in this article, we focus on how varying levels of right-wing authoritarian tendencies relate to the dissemination of COVID-19 vaccine related misinformation.

4. With our experimental setup, we are trying to mimic fast-paced decision-making induced by social media feeds. To ensure that we record a decision for each given headline, we decided not to present the headlines in a real social media feed, which could have resulted in respondents scrolling down and ending the experiment without sharing any data with the researchers.

5. We measure support for governing parties rather than partisanship as political parties in Romania have a high degree of volatility for reasons of policy failure, ample party switching and clientelistic practices (Gherghina, 2014; Klein, 2019; Savage, 2016). The Hungarian party system, in turn, is polarized between Fidesz supporters (a party that has been continuously in government since 2010) and anti-Fidesz supporters who may support any other party. In both instances, support for the government in place presents a more relevant measure of political allegiances than partisanship.

Additional information

Funding

This work was supported by the HORIZON EUROPE European Research Council [885026]; Horizon 2020 Framework Programme [754388].

Notes on contributors

Julia Schulte-Cloos

Julia Schulte-Cloos is an Assistant Professor of Political Science at the University of Marburg. Her research interests include comparative politics, political behaviour, and computational social science.

Veronica Anghel

Veronica Anghel is a Lecturer of Political Science at the Johns Hopkins School of Advanced International Studies. Her research interests include comparative politics, international relations, risk modeling, European integration, and the politics of Central and Eastern Europe.