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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. |
条目包含的文件 | 条目无相关文件。 |
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