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Feed for good? On the effects of personalization algorithms in social platforms

Author

Listed:
  • Miguel Risco
  • Manuel Lleonart-Anguix

Abstract

This paper builds a theoretical model of communication and learning on a social media platform, and describes the algorithm an engagement-maximizing platform implements in equilibrium. Such algorithm excessively exploits similarity, locking users in echo chambers. Moreover, learning vanishes as platform size grows large. As this is far from ideal, we explore alternatives. The reverse-chronological algorithm the DSA mandated to reincorporate turns out to be not good enough, so we build the "breaking echo chambers" algorithm, a modification of the platform-optimal algorithm that improves learning by promoting opposite thoughts. Additionally, we seek a natural implementation path for the utilitarian optimal algorithm. This is why we advocate for horizontal interoperability, which interoperability compels platforms to compete based on algorithms. In the absence of platform-specific network effects that entrench users within dominant platforms, the retention of user bases hinges on implementing algorithms that outperform those of competitors.

Suggested Citation

  • Miguel Risco & Manuel Lleonart-Anguix, 2024. "Feed for good? On the effects of personalization algorithms in social platforms," CRC TR 224 Discussion Paper Series crctr224_2024_580, University of Bonn and University of Mannheim, Germany.
  • Handle: RePEc:bon:boncrc:crctr224_2024_580
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    File URL: https://www.crctr224.de/research/discussion-papers/archive/dp580
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    References listed on IDEAS

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    1. Matthew Ellman & Fabrizio Germano, 2009. "What do the Papers Sell? A Model of Advertising and Media Bias," Economic Journal, Royal Economic Society, vol. 119(537), pages 680-704, April.
    2. Mueller-Frank, Manuel & Neri, Claudia, 2021. "A general analysis of boundedly rational learning in social networks," Theoretical Economics, Econometric Society, vol. 16(1), January.
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    More about this item

    Keywords

    personalized feed; social learning; network effects; interoperability;
    All these keywords.

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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