IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2503.11561.html
   My bibliography  Save this paper

Algorithms vs. Peers: Shaping Engagement with Novel Content

Author

Listed:
  • Shan Huang
  • Yi Ji
  • Leyu Lin

Abstract

The pervasive rise of digital platforms has reshaped how individuals engage with information, with algorithms and peer influence playing pivotal roles in these processes. This study investigates the effects of algorithmic curation and peer influence through social cues (e.g., peer endorsements) on engagement with novel content. Through a randomized field experiment on WeChat involving over 2.1 million users, we find that while peer-sharing exposes users to more novel content, algorithmic curation elicits significantly higher engagement with novel content than peer-sharing, even when social cues are present. Despite users' preference for redundant and less diverse content, both mechanisms mitigate this bias, with algorithms demonstrating a stronger positive effect than peer influence. These findings, though heterogeneous, are robust across demographic variations such as sex, age, and network size. Our results challenge concerns about "filter bubbles" and underscore the constructive role of algorithms in promoting engagement with non-redundant, diverse content.

Suggested Citation

  • Shan Huang & Yi Ji & Leyu Lin, 2025. "Algorithms vs. Peers: Shaping Engagement with Novel Content," Papers 2503.11561, arXiv.org, revised Mar 2025.
    • Handle: RePEc:arx:papers:2503.11561
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2503.11561
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jing Peng & Christophe Van den Bulte, 2024. "Participation vs. Effectiveness in Sponsored Tweet Campaigns: A Quality-Quantity Conundrum," Management Science, INFORMS, vol. 70(11), pages 7961-7983, November.
    2. Susan Athey & Kristen Grabarz & Michael Luca & Nils Wernerfelt, 2023. "Digital public health interventions at scale: The impact of social media advertising on beliefs and outcomes related to COVID vaccines," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(5), pages 2208110120-, January.
    3. Leif Nelson & Duncan Simester & K. Sudhir, 2020. "Introduction to the Special Issue on Marketing Science and Field Experiments," Marketing Science, INFORMS, vol. 39(6), pages 1033-1038, November.
    4. Jie-Hao Shao & E. Zhang & Yi Xiang & Ran-Zhe Jing, 2024. "Efficient combinations of dual incentives on social networks to achieve viral spread," Electronic Commerce Research, Springer, vol. 24(4), pages 2381-2404, December.
    5. Ike Silver & Deborah A. Small, 2024. "Put Your Mouth Where Your Money Is: A Field Experiment Encouraging Donors to Share About Charity," Marketing Science, INFORMS, vol. 43(2), pages 392-406, March.
    6. Ratchford, Brian & Soysal, Gonca & Zentner, Alejandro & Gauri, Dinesh K., 2022. "Online and offline retailing: What we know and directions for future research," Journal of Retailing, Elsevier, vol. 98(1), pages 152-177.
    7. Susan Athey & Kristen Grabarz & Michael Luca & Nils Wernerfelt, 2022. "The Effectiveness of Digital Interventions on COVID-19 Attitudes and Beliefs," Papers 2206.10214, arXiv.org.
    8. Michael A. Wiles & Saeed Janani & Darima Fotheringham & Chadwick J. Miller, 2024. "A Longitudinal Examination of the Relationship Between National-Level Per Capita Advertising Expenditure and National-Level Life Satisfaction Across 76 Countries," Marketing Science, INFORMS, vol. 43(3), pages 542-563, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2503.11561. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.