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Published on: August 18, 2023
Conformity to popular, not average, opinions: Models, data, and evolution
Kaleda K Denton1, Marcus W Feldman2, Jonathan F Johannemann3
1Santa Fe Institute, Santa Fe, NM 87501.
Summary
Individuals may conform to peer opinions rather than averaging them, influencing group consensus. This conformity model better explains decision-making data and can lead to faster polarization than averaging models.
Area of Science:
- Social Psychology
- Network Science
- Computational Social Science
Background:
- Traditional models assume individuals average peer estimates (e.g., French-DeGroot learning).
- An alternative behavior is conformity, where individuals adopt existing opinion clusters.
- This study explores how personal beliefs and social information interact in conformity.
Purpose of the Study:
- To extend a conformity model with personal beliefs and social information.
- To compare the conformity model against French-DeGroot averaging models using human data.
- To simulate evolutionary dynamics of these models across various network structures.
Main Methods:
- Developed an extended conformity model incorporating personal beliefs and social influence.
- Evaluated model performance against two French-DeGroot averaging models using human decision-making data.
- Conducted evolutionary simulations on static and adaptive networks to analyze model dynamics.
Main Results:
- The conformity model significantly outperformed French-DeGroot models in fitting human decision-making data.
- Evolutionary simulations showed the conformity model can drive faster polarization toward extreme opinions.
- Conformity dynamics can potentially reduce average estimation accuracy within populations.
Conclusions:
- Conformity is a crucial mechanism in social learning, often outperforming simple averaging.
- The conformity model offers new insights into consensus formation, opinion polarization, and collective intelligence.
- Network structure significantly impacts the evolutionary trajectories of conformity and averaging behaviors.
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