Quantifying the impact of misinformation and vaccine-skeptical content on Facebook

Author:

Allen Jennifer1ORCID,Watts Duncan J.234ORCID,Rand David G.156ORCID

Affiliation:

1. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.

2. Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA.

3. Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA.

4. Operations, Information, and Decisions Department, University of Pennsylvania, Philadelphia, PA, USA.

5. Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA.

6. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.

Abstract

Low uptake of the COVID-19 vaccine in the US has been widely attributed to social media misinformation. To evaluate this claim, we introduce a framework combining lab experiments (total N = 18,725), crowdsourcing, and machine learning to estimate the causal effect of 13,206 vaccine-related URLs on the vaccination intentions of US Facebook users ( N ≈ 233 million). We estimate that the impact of unflagged content that nonetheless encouraged vaccine skepticism was 46-fold greater than that of misinformation flagged by fact-checkers. Although misinformation reduced predicted vaccination intentions significantly more than unflagged vaccine content when viewed, Facebook users’ exposure to flagged content was limited. In contrast, unflagged stories highlighting rare deaths after vaccination were among Facebook’s most-viewed stories. Our work emphasizes the need to scrutinize factually accurate but potentially misleading content in addition to outright falsehoods.

Publisher

American Association for the Advancement of Science (AAAS)

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