| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w28465 |
| 来源ID | Working Paper 28465 |
| Learning from Shared News: When Abundant Information Leads to Belief Polarization | |
| Renee Bowen; Danil Dmitriev; Simone Galperti | |
| 发表日期 | 2021-02-15 |
| 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. We find that news aggregators can curb polarization caused by news sharing. Our results hold without media bias or fake news, so eliminating these is not sufficient to reduce polarization. When fake news is included, it can lead to polarization but only through misperceived selective sharing. We apply our theory to shed light on the evolution of public opinions about climate change in the US. |
| 主题 | Microeconomics ; Economics of Information ; Behavioral Economics |
| URL | https://www.nber.org/papers/w28465 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/586138 |
| 推荐引用方式 GB/T 7714 | Renee Bowen,Danil Dmitriev,Simone Galperti. Learning from Shared News: When Abundant Information Leads to Belief Polarization. 2021. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w28465.pdf（1168KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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