全球智库信息集成服务系统(G2TT): DP15789 Learning from Shared News: When Abundant Information Leads to Belief Polarization

G2TT

来源类型	Discussion paper
规范类型	论文
来源ID	DP15789
	DP15789 Learning from Shared News: When Abundant Information Leads to Belief Polarization
	T. Renee Bowen; Simone Galperti; Danil Dmitriev
发表日期	2021-02-09
出版年	2021
语种	英语
摘要	We study learning via shared news. Each period agents receive the same quantity and quality of first-hand information and can share it with friends. Some friends (possibly few) share selectively, generating heterogeneous news diets across agents akin to echo chambers. Agents are aware of selective sharing and update beliefs by Bayes’ rule. Contrary to standard learning results, we show that beliefs can diverge in this environment leading to polarization. This requires that (i) agents hold misperceptions (even minor) about friends’ sharing and (ii) information quality is sufficiently low. Polarization can worsen when agents’ social connections expand. When the quantity of first-hand information becomes large, agents can hold opposite extreme beliefs resulting in severe polarization. Our results hold without media bias or fake news, so eliminating these is not sufficient to reduce polarization. When fake news is included, we show that it can lead to polarization but only through misperceived selective sharing. News aggregators can curb polarization caused by shared news.
主题	Public Economics
关键词	Polarization Echo chamber Selective sharing Learning Information Fake news Misspecification
URL	https://cepr.org/publications/dp15789
来源智库	Centre for Economic Policy Research (United Kingdom)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/544789
推荐引用方式 GB/T 7714	T. Renee Bowen,Simone Galperti,Danil Dmitriev. DP15789 Learning from Shared News: When Abundant Information Leads to Belief Polarization. 2021.