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- Title
Dynamic Opinion Aggregation: Long-Run Stability and Disagreement.
- Authors
Cerreia-Vioglio, Simone; Corrao, Roberto; Lanzani, Giacomo
- Abstract
This article proposes a model of non-Bayesian social learning in networks that accounts for heuristics and biases in opinion aggregation. The updating rules are represented by non-linear opinion aggregators from which we extract two extreme networks capturing strong and weak links. We provide graph-theoretic conditions for these networks that characterize opinions' convergence, consensus formation, and efficient or biased information aggregation. Under these updating rules, agents may ignore some of their neighbours' opinions, reducing the number of effective connections and inducing long-run disagreement for finite populations. For the wisdom of the crowd in large populations, we highlight a trade-off between how connected the society is and the non-linearity of the opinion aggregator. Our framework bridges several models and phenomena in the non-Bayesian social learning literature, thereby providing a unifying approach to the field.
- Subjects
CONSENSUS (Social sciences); SWARM intelligence; SOCIAL learning; SOCIAL networks; SOCIAL facts
- Publication
Review of Economic Studies, 2024, Vol 91, Issue 3, p1406
- ISSN
0034-6527
- Publication type
Article
- DOI
10.1093/restud/rdad072