The Burden of Social Proof: Shared Thresholds and Social Influence

[Correction Notice: An erratum for this article was reported in Vol 119(2) of Psychological Review (see record 2012-06153-001). In the article, incorrect versions of figures 3 and 6 were included. Also, Table 8 should have included the following information in the table footnote "P(A V) = proba...

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Bibliographic Details
Published in:Psychological review 2012-04, Vol.119 (2), p.345-372
Main Author: MacCoun, Robert J
Format: Article
Language:English
Subjects:
Biological and medical sciences
Comparative Analysis
Computer Simulation
Conformity (Personality)
Consensus
Family
Fundamental and applied biological sciences. Psychology
Helping Behavior
Human
Humans
Imitative Behavior
Item Response Theory
Leadership
Mass Behavior
Models, Theoretical
Monte Carlo Methods
Probability
Psychological Studies
Psychology
Psychology, Social - statistics & numerical data
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Social Behavior
Social Change
Social Conformity
Social Influences
Social interactions. Communication. Group processes
Social psychology
Theories
Thresholds
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Summary:[Correction Notice: An erratum for this article was reported in Vol 119(2) of Psychological Review (see record 2012-06153-001). In the article, incorrect versions of figures 3 and 6 were included. Also, Table 8 should have included the following information in the table footnote "P(A V) = probability of acquittal given unanimous verdict." All versions of this article have been corrected.] Social influence rises with the number of influence sources, but the proposed relationship varies across theories, situations, and research paradigms. To clarify this relationship, I argue that people share some sense of where the "burden of social proof" lies in situations where opinions or choices are in conflict. This suggests a family of models sharing 2 key parameters, one corresponding to the location of the influence threshold, and the other reflecting its clarity--a factor that explains why discrete "tipping points" are not observed more frequently. The plausibility and implications of this account are examined using Monte Carlo and cellular automata simulations and the relative fit of competing models across classic data sets in the conformity, group deliberation, and social diffusion literatures. (Contains 18 footnotes, 10 tables, and 11 figures.)
ISSN:0033-295X
1939-1471
DOI:10.1037/a0027121