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Article . 2022 . Peer-reviewed
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Combining Refutations and Social Norms Increases Belief Change

Authors: Ullrich K. H. Ecker; Jasmyne Sanderson; Paul McIlhiney; Jessica Rowsell; Hayley Quekett; Gordon Brown; Stephan Lewandowsky;

Combining Refutations and Social Norms Increases Belief Change

Abstract

Misinformed beliefs are difficult to change. Refutations that target false claims typically reduce false beliefs, but tend to be only partially effective. In this study, a social norming approach was explored to test whether provision of peer norms could provide an alternative or complementary approach to refutation. Three experiments investigated whether a descriptive norm—by itself or in combination with a refutation—could reduce the endorsement of worldview-congruent claims. Experiment 1 found that using a single point estimate to communicate a norm affected belief but had less impact than a refutation. Experiment 2 used a verbally-presented distribution of four values to communicate a norm, which was largely ineffective. Experiment 3 used a graphically-presented social norm with 25 values, which was found to be as effective at reducing claim belief as a refutation, with the combination of both interventions being most impactful. These results provide a proof of concept that normative information can aid in the debunking of false or equivocal claims, and suggests that theories of misinformation processing should take social factors into account.

Country
United Kingdom
Keywords

/dk/atira/pure/core/keywords/tedcog, Continued influence effect, 330, Communication, Cognitive Psychology, debunking, belief change, Reasoning, Social and Behavioral Sciences, false beliefs, 004, /dk/atira/pure/core/keywords/cognitive_science, Memory, /dk/atira/pure/core/keywords/tedcog; name=TeDCog, name=Cognitive Science, Social Norms, /dk/atira/pure/core/keywords/cognitive_science; name=Cognitive Science, Humans, name=TeDCog, misinformation, social norms

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    Top 10%
    influence
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    impulse
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Average
Top 10%
Green
hybrid