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Integration of Social Information by Human Groups
Boris Granovskiy1, Jason M Gold2, David J T Sumpter1
1Department of Mathematics, Uppsala University, Institute for Futures Studies, Stockholm.
Topics in Cognitive Science
|July 21, 2015
Summary
The wisdom of crowds improves group trivia performance with size, but individuals tend toward moderate answers. Social information helps correct extreme outliers, enhancing group accuracy when initial guesses are biased.
Area of Science:
- Cognitive Psychology
- Social Psychology
- Behavioral Economics
Background:
- The wisdom of crowds theory suggests group averages can be accurate estimates.
- Key conditions for wisdom of crowds include independent and unbiased estimates.
- Individuals often lack direct feedback on decision accuracy, relying on social cues.
Purpose of the Study:
- To investigate how individuals integrate social information when answering quantitative trivia questions.
- To examine the impact of group size and social influence on decision accuracy.
- To identify biases in individual estimation and their effect on group performance.
Main Methods:
- Participants answered trivia questions with percentage-based answers (0-100%).
- Social information from peer group estimates was provided.
- A mathematical model was developed to simulate cognitive processes of social information integration.
Main Results:
- Group performance improved with increased group size, supporting the wisdom of crowds.
- Individuals exhibited a bias towards insufficiently extreme estimates, moving towards the group mean.
- Social information improved group performance by reducing the impact of outliers, especially when initial guesses were biased.
Conclusions:
- Individuals adjust their estimates based on peer information, a process modeled by a cognitive decision to integrate social cues.
- This social influence can lead to group polarization away from 50% and systematic removal of outlying incorrect opinions.
- While social information offers improvement, it is most effective when initial individual estimates are biased.
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