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How minimizing conflicts could lead to polarization on social media: An agent-based model investigation

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  • Michele Coscia
  • Luca Rossi

Abstract

Social media represent an important source of news for many users. They are, however, affected by misinformation and they might be playing a role in the growth of political polarization. In this paper, we create an agent based model to investigate how policing content and backlash on social media (i.e. conflict) can lead to an increase in polarization for both users and news sources. Our model is an advancement over previously proposed models because it allows us to study the polarization of both users and news sources, the evolution of the audience connections between users and sources, and it makes more realistic assumptions about the starting conditions of the system. We find that the tendency of users and sources to avoid policing, backlash and conflict in general can increase polarization online. Specifically polarization comes from the ease of sharing political posts, intolerance for opposing points of view causing backlash and policing, and volatility in changing one’s opinion when faced with new information. On the other hand, it seems that the integrity of a news source in trying to resist the backlash and policing has little effect.

Suggested Citation

  • Michele Coscia & Luca Rossi, 2022. "How minimizing conflicts could lead to polarization on social media: An agent-based model investigation," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-23, January.
    • Handle: RePEc:plo:pone00:0263184
    DOI: 10.1371/journal.pone.0263184
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    References listed on IDEAS

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    1. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    2. Charles S. Taber & Milton Lodge, 2006. "Motivated Skepticism in the Evaluation of Political Beliefs," American Journal of Political Science, John Wiley & Sons, vol. 50(3), pages 755-769, July.
    3. Kazutoshi Sasahara & Wen Chen & Hao Peng & Giovanni Luca Ciampaglia & Alessandro Flammini & Filippo Menczer, 2021. "Social influence and unfollowing accelerate the emergence of echo chambers," Journal of Computational Social Science, Springer, vol. 4(1), pages 381-402, May.
    4. Christopher A. Bail & Lisa P. Argyle & Taylor W. Brown & John P. Bumpus & Haohan Chen & M. B. Fallin Hunzaker & Jaemin Lee & Marcus Mann & Friedolin Merhout & Alexander Volfovsky, 2018. "Exposure to opposing views on social media can increase political polarization," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(37), pages 9216-9221, September.
    5. Ro'ee Levy, 2021. "Social Media, News Consumption, and Polarization: Evidence from a Field Experiment," American Economic Review, American Economic Association, vol. 111(3), pages 831-870, March.
    6. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    7. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
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