Working Paper: CEPR ID: DP15789
Authors: T. Renee Bowen; Simone Galperti; Danil Dmitriev
Abstract: 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.
Keywords: polarization; echo chamber; selective sharing; learning; information quality; fake news; misspecification
JEL Codes: D82; D83; D90
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| selective sharing (D16) | divergent beliefs (Z12) |
| misperceptions about sharing (D16) | divergent beliefs (Z12) |
| low information quality (L15) | divergent beliefs (Z12) |
| misperceptions about sharing and low information quality (D83) | polarization (C46) |
| expanding social connections (Z13) | increased polarization (F69) |
| fake news (Y50) | increased polarization (F69) |
| news aggregators (C43) | reduced polarization (F69) |