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Social influence and unfollowing accelerate the emergence of echo chambers

Author

Listed:
  • Kazutoshi Sasahara

    (Nagoya University
    JST PRESTO
    Indiana University Bloomington)

  • Wen Chen

    (Indiana University Bloomington
    Indiana University)

  • Hao Peng

    (Indiana University
    University of Michigan)

  • Giovanni Luca Ciampaglia

    (Indiana University
    University of South Florida)

  • Alessandro Flammini

    (Indiana University Bloomington
    Indiana University
    Indiana University)

  • Filippo Menczer

    (Indiana University Bloomington
    Indiana University
    Indiana University)

Abstract

While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as “echo chambers.” Here we study the conditions in which such echo chambers emerge by introducing a simple model of information sharing in online social networks with the two ingredients of influence and unfriending. Users can change both their opinions and social connections based on the information to which they are exposed through sharing. The model dynamics show that even with minimal amounts of influence and unfriending, the social network rapidly devolves into segregated, homogeneous communities. These predictions are consistent with empirical data from Twitter. Although our findings suggest that echo chambers are somewhat inevitable given the mechanisms at play in online social media, they also provide insights into possible mitigation strategies.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jcsosc:v:4:y:2021:i:1:d:10.1007_s42001-020-00084-7
    DOI: 10.1007/s42001-020-00084-7
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    References listed on IDEAS

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    1. Alexander J. Stewart & Mohsen Mosleh & Marina Diakonova & Antonio A. Arechar & David G. Rand & Joshua B. Plotkin, 2019. "Information gerrymandering and undemocratic decisions," Nature, Nature, vol. 573(7772), pages 117-121, September.
    2. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
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    Cited by:

    1. 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.
    2. Muhammad Al Atiqi & Shuang Chang & Hiroshi Deguchi, 2023. "Simulating the influence of Facebook fan pages on individual attitudes toward vaccination using agent‐based modelling," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(3), pages 595-610, May.
    3. Wu, Yue & Li, Linjiao & Yu, Qiannan & Gan, Jiaxin & Zhang, Yi, 2023. "Strategies for reducing polarization in social networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    4. Ni, Xuelian & Xiong, Fei & Pan, Shirui & Chen, Hongshu & Wu, Jia & Wang, Liang, 2023. "How heterogeneous social influence acts on human decision-making in online social networks," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    5. Saeed Badri & Bernd Heidergott & Ines Lindner, 2022. "Na?ve Learning in Social Networks with Fake News: Bots as a Singularity," Tinbergen Institute Discussion Papers 22-097/II, Tinbergen Institute.
    6. 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).

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