A mathematical model for social influences on perceptual judgments

Kriss, Mitchel; Kinchla, R. A.; Darley, John M.

doi:10.1016/0022-1031(77)90026-9

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…This correlation between members is confined by assumption to the individual's perceptual stage of processing; that is, it is present earlier than the group decision stage of the system shown in Figures 2 and 3. Conversely, the influence of one member on another is confined to the decision stage of the system, specifically, the setting of decision weights on each member's contribution to the group decision (e.g., Kriss, Kinchla, & Darley, 1977; Robinson & Sorkin, 1985).…”

Section: Discussionmentioning

confidence: 99%

Signal-detection analysis of group decision making.

Sorkin

Hays²,

West³

2001

Psychological Review

195

222

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How effectively can groups of people make yes-or-no decisions? To answer this question, we used signal-detection theory to model the behavior of groups of human participants in a visual detection task. The detection model specifies how performance depends on the group's size, the competence of the members, the correlation among members' judgments, the constraints on member interaction, and the group's decision rule. The model also allows specification of performance efficiency, which is a measure of how closely a group's performance matches the statistically optimal group. The performance of our groups was consistent with the theoretical predictions, but efficiency decreased as group size increased. This result was attributable to a decrease in the effort that members gave to their individual tasks rather than to an inefficiency in combining the information in the members' judgments.

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Section: Discussionmentioning

confidence: 99%

Signal-detection analysis of group decision making.

Sorkin

Hays²,

West³

2001

Psychological Review

195

222

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show abstract

“…1Signal detection models have also been applied to persuasion and group judgment (e.g., Kriss, Kinchla, & Darley, 1977; Sorkin, Hays, & West, 2001), but these applications are quite different than the social thresholds proposed here.…”

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confidence: 99%

The burden of social proof: Shared thresholds and social influence.

MacCoun

2012

Psychological Review

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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.

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“…Thus, computers have been utilized to study interpersonal referential communication (van Rooijen & Goode, 1973), bargaining and coalition formation (Flaherty, 1976;Rapoport & Kahan, 1974;Shure, Meeker, & Hansford, 1965), consequences of stimulus familiarity (Stang & O'Connell, 1974), interpersonal attraction (Evans & Dabbs, 1975), conformity (Kris, Kinchla, & Darley, 1977;Seligman & Stang, 1975), and susceptibility to persuasive communication (Ronis, Baumgardner, Leippe, Cacioppo, & Greenwald,1977).…”

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confidence: 99%