Information Aggregation and Social Networks: Responsiveness and Overturning

Shinpei Noguchi, Hiroto Sato and Konan Shimizu

Papers from arXiv.org

Abstract: This paper studies how network structures affect the efficiency of information aggregation in social learning environments. We consider a model in which rational agents sequentially choose actions based on private signals and observations of their neighbors' actions in a network. Focusing on comparisons of expected payoffs at a given finite period, we show that there exists an information structure under which the star network achieves a strictly higher expected payoff than any other network, and another information structure under which the complete network achieves a strictly higher expected payoff than any other network. Taken together, these results imply that no network is uniformly optimal across all information structures. Our analysis highlights a trade-off between the responsiveness effect and the overturning effect: disconnected networks preserve responsiveness of actions to private signals, whereas highly connected networks facilitate the aggregation of extreme information that overturns public beliefs.

Date: 2026-07
References: Add references at CitEc
Citations:

Downloads: (external link)
https://arxiv.org/pdf/2607.28921 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2607.28921

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().