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Privacy and Polarization: An Inference-Based Framework

Author

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  • Tommaso Bondi

    (Marketing, Cornell Tech and SC Johnson College of Business, Cornell University, New York, New York 10044)

  • Omid Rafieian

    (Marketing, Cornell Tech and SC Johnson College of Business, Cornell University, New York, New York 10044)

  • Yunfei (Jesse) Yao

    (The Chinese University of Hong Kong, Shatin, Hong Kong)

Abstract

Advances in behavioral targeting allow media firms to better monetize based on advertising. However, behavioral ad targeting requires consumer tracking, which has heightened privacy concerns among consumers and regulators. We examine how stricter privacy regulations that ban consumer tracking affect media firms’ content strategies and ideological positioning. We consider a model where media firms choose their ideological positioning and advertising, whereas ideologically heterogeneous consumers select their preferred content based on both their ideology and idiosyncratic taste shocks. We compare two salient informational environments: (1) behavioral ad targeting, where perfect inference about consumers is allowed, and (2) contextual ad targeting, where consumer tracking is banned due to privacy regulations, and media firms can only infer consumer types based on their media choice. We show that privacy regulations that ban behavioral ad targeting incentivize media firms to shift toward more extreme and polarizing positioning in order to draw better inferences about consumer types, even though the shift to more extreme ideological positions can hurt both demand and consumer welfare from content consumption. Compared with the monopoly case, competition increases firms’ inference motives and leads to more polarized content over a wider range of parameters due to an inferential complementarity effect arising from consumer self-selection. Our research uncovers a previously unexplored relationship between privacy and polarization, shedding light on the potential unintended consequences of privacy regulations in media markets.

Suggested Citation

  • Tommaso Bondi & Omid Rafieian & Yunfei (Jesse) Yao, 2026. "Privacy and Polarization: An Inference-Based Framework," Management Science, INFORMS, vol. 72(2), pages 1389-1409, February.
  • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:2:p:1389-1409
    DOI: 10.1287/mnsc.2024.06054
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