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News Customization with AI

Author

Listed:
  • Felix Chopra
  • Ingar K. Haaland
  • Fabian Roeben
  • Christopher Roth
  • Vanessa Sticher

Abstract

News outlets compete for engagement rather than reader satisfaction, leading to persistent mismatches between consumer demand and the supply of news. We test whether offering people the opportunity to customize the news can address this mismatch by unbundling presentation from coverage. In our AI-powered news app, users can customize article characteristics, such as the complexity of the writing or the extent of opinion, while holding the underlying news event constant. Using rich news consumption data from large-scale field experiments, we uncover substantial heterogeneity in news preferences. While a significant fraction of users demand politically aligned news, the vast majority of users display a high and persistent demand for less opinionated and more fact-driven news. Customization also leads to a better match between the news consumed and stated preferences, increasing news satisfaction.

Suggested Citation

  • Felix Chopra & Ingar K. Haaland & Fabian Roeben & Christopher Roth & Vanessa Sticher, 2025. "News Customization with AI," CESifo Working Paper Series 12121, CESifo.
    • Handle: RePEc:ces:ceswps:_12121
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    1. Luca Braghieri & Ro'ee Levy & Hannah Trachtman, 2025. "Frictions in News Consumption: How to Improve the Social Media News Diet," EconPol Forum, CESifo, vol. 26(04), pages 12-16, October.

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    Keywords

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    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • P00 - Political Economy and Comparative Economic Systems - - General - - - General

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