We study social learning via news sharing. Each period agents receive the same quantity and quality of first-hand information and have the opportunity to share it with friends. Some agents (possibly a few) share information selectively. Selective sharing generates heterogeneous news diets across agents, who, however, are aware of it and update beliefs via Bayes’ rule. We show that, contrary to standard learning results, agents’ beliefs can diverge in this environment. This occurs if and only if agents hold misperceptions (even minor) about friends’ access to first-hand information and if its quality is low. We show that abundant information can exacerbate belief polarization. That is, when the quantity of first-hand information grows indefinitely agents can hold opposite degenerate beliefs. Intuitively, polarization worsens with misperception and imbalance of news diets. Polarization can also worsen when information quality rises or when the agents’ social networks expand, despite providing them with more information. Information aggregation can mitigate, and even eliminate, polarization.
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