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How Right-Leaning Media Coverage of COVID-19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic in the U.S.

Published online by Cambridge University Press:  01 May 2020

Matt Motta*
Affiliation:
Department of Political Science, Oklahoma State University, 210 Murray Hall, Stillwater, OK74078, USA
Dominik Stecula
Affiliation:
Annenberg Public Policy Center, University of Pennsylvania, 202 S 36 St. Philadelphia, PA19104, USA Centre for Public Opinion and Political Representation, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada
Christina Farhart
Affiliation:
Department of Political Science, Carleton College, Willis Hall #415, Northfield, MN55057, USA
*
*Corresponding author. Email: matthew.motta@okstate.edu
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Extract

We have yet to know the ultimate global impact of the novel coronavirus pandemic. However, we do know that delays, denials and misinformation about COVID-19 have exacerbated its spread and slowed pandemic response, particularly in the U.S. (e.g., Abutaleb et al., 2020).

Information

Type
Research Note/Notes de recherche
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Canadian Political Science Association (l'Association canadienne de science politique) and/et la Société québécoise de science politique 2020
Figure 0

Figure 1. Prevalence of COVID-19 misinformation on right-leaning vs. mainstream media (February 1–March 23, 2020).

Note: Story counts are derived from queries of the MediaCloud Explorer database. Search terms included (“coronavirus” OR “covid”) and (“made in a lab” OR “Big Pharma” OR “George Soros” OR “hoax” OR “conspiracy” OR “bioweapon” OR “not real” OR “existing vaccine”). Please refer to the Methods section in the online Appendix for additional information about MediaCloud and our search protocol.
Figure 1

Figure 2. COVID-19 misinformation endorsement (March 10–16, 2020).

Note: Bars correspond to the weighted percentage of survey respondents in Pew's nationally representative ATP Wave 63.5 Survey (N = 8,914). Misinformation indicators are derived from responses to two questions. First, respondents were asked if they think “it is most likely that the current strain of the coronavirus” was either “developed intentionally in a lab,” “made accidentally in a lab,” “came about naturally,” or “does not exist.” From this, we created three dichotomous variables taking on values of 1 if respondents believe that COVID-19 was lab created (1) accidentally, (2) on purpose, (3) or if they believe that the virus does not exist. Respondents were also asked whether or not a COVID-19 vaccine is available “now,” “in the next few months,” “in a year or more,” or that “it is not possible to create a vaccine.” From this, we created a fourth dichotomous indicator, with those indicating that the vaccine is available now or will be available in the next few months scored as being misinformed.
Figure 2

Figure 3. Correlates of misinformation endorsement (March 10–16, 2020).

Note: Logistic regression parameter estimates presented (shaded circles), with 95 per cent confidence intervals extending out from each one (N = 6,266). Note that, in order to avoid endogeneity concerns, antiscientist and antijournalist attitudes were measures prior to Wave 63.5 (ATP Wave 40, Fall 2019). Due to panel attrition, we lose N = 1,914. Note also that we do not include the “COVID-19 does not exist” misinformation indicator in these analyses, as fewer than 1 per cent of the sample endorsed this view (N = 56). Additional information about the ATP sample, how each control variable in the model was measured, and how we address potential endogeneity concerns can be found in the Methods section in the online Appendix. All data are weighted.
Figure 3

Figure 4. The effect of misinformation endorsement on anti-CDC attitudes (March 10–16, 2020).

Note: N = 8,568. Predicted probabilities (bars), with 95 per cent confidence intervals (lines). The outcome variable in this analysis is an indicator of whether or not respondents think that the CDC “greatly” or “slightly” exaggerated COVID-19's health risks. Probabilities were calculated based on the results of a logistic regression model, holding all covariates at their sample means. The model controls for all factors displayed in Figure 2, with the exception that we remove antiscientist and antijournalist views from these models (due to concerns of a lack of conceptual distinctness between these variables and the outcome variable). As a result, the valid N for this model is larger than the model results presented in Figure 2. Note also that we again exclude the “COVID-19 does not exist” variable from these analyses (see the note accompanying Figure 2). Additional information about how we measured the outcome variable in this analysis, as well as all independent variables, can be found in the “Online Methods” section of the online Appendix. All data are weighted.
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