Privacy and Polarization: An Inference-Based Approach

Tommaso Bondi () and Omid Rafieian ()
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Tommaso Bondi: Cornell Tech, 2 West Loop Road, 10044 New York, NY
Omid Rafieian: Cornell Tech, 2 West Loop Road, 10044 New York, NY

No 23-09, Working Papers from NET Institute

Abstract: Advances in behavioral targeting allow news publishers to monetize based on advertising. However, behavioral targeting requires consumer tracking, which has heightened privacy concerns among consumers and regulators. In this paper, we examine how stricter privacy regulations that ban consumer tracking affect news publishers' content strategies. We develop a theoretical framework that captures a change in privacy policies as a shift in publishers' inference about consumer types. We consider a model where news publishers choose the content and advertising, and ideologically heterogeneous consumers select their preferred content based on their ideology and idiosyncratic shocks. We compare two salient informational environments: (1) behavioral targeting, where perfect inference about consumers is allowed, and (2) contextual targeting, where consumer tracking is banned due to privacy regulations, and publishers can only infer consumer types based on their content choice. We show that privacy regulations that ban behavioral targeting incentivize publishers to shift towards more extreme and polarizing content in both monopoly and duopoly settings, even though the shift to more extreme content can hurt both demand and consumer welfare. In summary, our research uncovers a previously unexplored relationship between privacy and polarization, shedding light on the potential unintended consequences of privacy regulations in media markets.

Keywords: advertising; targeting; privacy; polarization (search for similar items in EconPapers)
JEL-codes: D83 L13 L82 M37 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2023-10
New Economics Papers: this item is included in nep-mic and nep-reg
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