Dynamic Opinion Aggregation: Long-Run Stability and Disagreement

• 成果类型: Article; Early Access
• 署名作者: Cerreia-Vioglio, Simone; Corrao, Roberto; Lanzani, Giacomo
• 署名单位: Bocconi University; Massachusetts Institute of Technology (MIT)
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.1093/restud/rdad072
• 发表日期: 2023
• 关键词: multiagent systems; social-influence; networks; consensus; COMMUNICATION; CONVERGENCE; probability; ambiguity

摘要

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.