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Polarized information ecosystems can reorganize social networks via information cascades

Author

Listed:
  • Christopher K. Tokita

    (a Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544;)

  • Andrew M. Guess

    (b Department of Politics, Princeton University, Princeton, NJ 08544;; c School of Public and International Affairs, Princeton University, Princeton, NJ 08544)

  • Corina E. Tarnita

    (a Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544;)

Abstract

Many argue that partisan media coverage creates political polarization by pushing people’s opinions to extremes, but evidence is mixed. We instead propose that partisan media coverage can cause polarization by altering people’s social connections and reorganizing social networks along political lines. Using computational modeling and social media data, we explore how people may adjust their social ties to avoid the sharing behavior of friends who might be engaging with news from nonpreferred information sources. Our model suggests that polarization is driven to a large extent by unfollowing, which can gradually—and inadvertently—produce homogeneous online networks, known to reduce exposure to challenging information and encourage outgroup hostility. In this way, institutional polarization can reverberate through the networked mass public.

Suggested Citation

  • Christopher K. Tokita & Andrew M. Guess & Corina E. Tarnita, 2021. "Polarized information ecosystems can reorganize social networks via information cascades," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(50), pages 2102147118-, December.
    • Handle: RePEc:nas:journl:v:118:y:2021:p:e2102147118
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    Citations

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    Cited by:

    1. Pérez-Martínez, H. & Bauzá Mingueza, F. & Soriano-Paños, D. & Gómez-Gardeñes, J. & Floría, L.M., 2023. "Polarized opinion states in static networks driven by limited information horizons," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    2. Zhang, Zhiwei & Liu, Gao & Chen, Bin & Huang, Kun, 2022. "Social asset or social liability? How partisanship moderates the relationship between social capital and Covid-19 vaccination rates across United States counties," Social Science & Medicine, Elsevier, vol. 311(C).
    3. Koguchi, Teppei & Jitsuzumi, Toshiya, 2024. "An international comparative analysis of the acceptability of the concept of "information health"," 24th ITS Biennial Conference, Seoul 2024. New bottles for new wine: digital transformation demands new policies and strategies 302508, International Telecommunications Society (ITS).
    4. Evan F. Kuehn, 2023. "The information ecosystem concept in information literacy: A theoretical approach and definition," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(4), pages 434-443, April.
    5. Martin-Gutierrez, Samuel & Losada, Juan C. & Benito, Rosa M., 2023. "Multipolar social systems: Measuring polarization beyond dichotomous contexts," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).

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