How to unring the bell: A meta-analytic approach to correction of misinformation

By Nathan Walter, Sheila T. Murphy. 2018

437 citations recorded by the source corpus.

Subfields: Communication, Literature and Literary Theory, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/dca8259bd6ca538809c4233208e75e12ed1be72c

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Citations in the corpus

Creating News Literacy Messages to Enhance Expert Corrections of Misinformation on Twitter (2020, background): “…to the NL message used here— may be less effective than specific corrective responses and sometimes generate cynicism toward all information rather than helping people distinguish misinformation from other types of content (Clayton et al., 2019; Pennycook & Rand, 2017; Walter & Murphy, 2018).”
Fact-Checking: A Meta-Analysis of What Works and for Whom (2019, background): “In comparison to the weak effects recorded in the current study, other meta-analyses observed strong (Blank & Launay, 2014; Chan et al., 2017) and moderate effects (Walter & Murphy, 2018).”
Fake news game confers psychological resistance against online misinformation (2019, methodology): “For the question about discrediting we used a different non-existent news site (“International Post Online”), employing an ad hominem (Walton, 1998) argument against the mainstream media: The Mainstream Media has been caught in so many lies that it can’t be trusted as a reliable news source.”
Countering Misinformation and Fake News Through Inoculation and Prebunking (2021, background): “…under 7.6% (Epstein & Robertson, 2015) and the 2016 election was decided by razor-thin margins in a few swing states), these effects can be considered meaningful when scaled (Funder & Ozer, 2019) and commensurate with effect sizes in persuasion research (Banas & Rains, 2010; Walter & Murphy, 2018).”
Evaluating the Impact of Attempts to Correct Health Misinformation on Social Media: A Meta-Analysis (2020, result): “Importantly, the pooled-effect retrieved in this study was comparable with previous meta-analyses that focused on the correction of misinformation in contexts such as crime, politics, and science (Walter et al., 2020; Walter & Murphy, 2018).”
A Meta-Analytic Examination of the Continued Influence of Misinformation in the Face of Correction: How Powerful Is It, Why Does It Happen, and How to Stop It? (2019, background): “Past meta-analyses examining the effect of correction compared with uncorrected misinformation control conditions have found that corrective messages can, indeed, significantly reduce belief in misinformation (Blank & Launay, 2014; Walter & Murphy, 2018).”
Correction Experiences on Social Media During COVID-19 (2021, methodology): “…Nyhan et al., 2014; Nyhan & Reifler, 2010), meta-analyses of this type of responsive correction have demonstrated that it is consistent if modestly effective (Walter & Murphy, 2018), including specifically in the domain of correction of health misinformation on social media (Walter et al., 2020).”
How Trust in Experts and Media Use Affect Acceptance of Common Anti-Vaccination Claims (2020, positive): “As meta-analyses confirm, correcting mistaken beliefs is difficult (Chan, Jones, Jamieson, & Albarracín, 2017; Walter & Murphy, 2018).”