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Millions of online book co-purchases reveal partisan differences in the consumption of science

Author

Listed:
  • Feng Shi

    (Computation Institute, University of Chicago)

  • Yongren Shi

    (Yale Institute for Network Science, Yale University)

  • Fedor A. Dokshin

    (Cornell University)

  • James A. Evans

    (Computation Institute, University of Chicago
    University of Chicago)

  • Michael W. Macy

    (Cornell University)

Abstract

Passionate disagreements about climate change, stem cell research and evolution raise concerns that science has become a new battlefield in the culture wars. We used data derived from millions of online co-purchases as a behavioural indicator for whether shared interest in science bridges political differences or selective attention reinforces existing divisions. Findings reveal partisan preferences both within and across scientific disciplines. Across fields, customers for liberal or ‘blue’ political books prefer basic science (for example, physics, astronomy and zoology), whereas conservative or ‘red’ customers prefer applied and commercial science (for example, criminology, medicine and geophysics). Within disciplines, ‘red’ books tend to be co-purchased with a narrower subset of science books on the periphery of the discipline. We conclude that the political left and right share an interest in science in general, but not science in particular. This underscores the need for research into remedies that can attenuate selective exposure to ‘convenient truth’, renew the capacity for science to inform political debate and temper partisan passions.

Suggested Citation

  • Feng Shi & Yongren Shi & Fedor A. Dokshin & James A. Evans & Michael W. Macy, 2017. "Millions of online book co-purchases reveal partisan differences in the consumption of science," Nature Human Behaviour, Nature, vol. 1(4), pages 1-9, April.
  • Handle: RePEc:nat:nathum:v:1:y:2017:i:4:d:10.1038_s41562-017-0079
    DOI: 10.1038/s41562-017-0079
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    Cited by:

    1. Sabina J Sloman & Daniel M Oppenheimer & Simon DeDeo, 2021. "Can we detect conditioned variation in political speech? two kinds of discussion and types of conversation," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-28, February.
    2. Alex Luscombe & Kevin Dick & Kevin Walby, 2022. "Algorithmic thinking in the public interest: navigating technical, legal, and ethical hurdles to web scraping in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1023-1044, June.
    3. Stefan M. Herzog & Thomas T. Hills, 2019. "Mediation Centrality in Adversarial Policy Networks," Complexity, Hindawi, vol. 2019, pages 1-15, April.
    4. Hou, Lei & Huang, Yichen, 2024. "Optimizing the connectedness of recommendation networks for retrieval accuracy and visiting diversity of random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).

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