Evidence map›Paper›PMID 35972960›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Online engagement with 2020 election misinformation and turnout in the 2021 Georgia runoff election.

Jon Green, William Hobbs, Stefan McCabe, David Lazer

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Online engagement with 2020 election misinformation and turnout in the 2021 Georgia runoff election.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jon GreenNetwork Science Institute, Northeastern University, Boston, MA 02115.ORCID 0000-0002-6542-6745
William HobbsDepartment of Psychology, Cornell University, Ithaca, NY 14853.ORCID 0000-0002-6229-2753
Stefan McCabeNetwork Science Institute, Northeastern University, Boston, MA 02115.ORCID 0000-0002-7180-145X
David LazerNetwork Science Institute, Northeastern University, Boston, MA 02115.ORCID 0000-0002-7991-9110

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following the 2020 general election, Republican elected officials, including then-President Donald Trump, promoted conspiracy theories claiming that Joe Biden's close victory in Georgia was fraudulent. Such conspiratorial claims could implicate participation in the Georgia Senate runoff election in different ways-signaling that voting doesn't matter, distracting from ongoing campaigns, stoking political anger at out-partisans, or providing rationalizations for (lack of) enthusiasm for voting during a transfer of power. Here, we evaluate the possibility of any on-average relationship with turnout by combining behavioral measures of engagement with election conspiracies online and administrative data on voter turnout for 40,000 Twitter users registered to vote in Georgia. We find small, limited associations. Liking or sharing messages opposed to conspiracy theories was associated with higher turnout than expected in the runoff election, and those who liked or shared tweets promoting fraud-related conspiracy theories were slightly less likely to vote.

Indexed as

CommunicationFraudPoliticsGeorgiaHumansLongitudinal StudieselectionsmisinformationturnoutTwitter

Identifiers

PMID35972960
PMCPMC9407668

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.