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Empirical social triad statistics can be explained with dyadic homophylic interactions

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  • Tuan Minh Pham

    (a Section for the Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, A-1090 Vienna, Austria;; b Complexity Science Hub, A-1090 Vienna, Austria;)

  • Jan Korbel

    (a Section for the Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, A-1090 Vienna, Austria;; b Complexity Science Hub, A-1090 Vienna, Austria;)

  • Rudolf Hanel

    (a Section for the Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, A-1090 Vienna, Austria;; b Complexity Science Hub, A-1090 Vienna, Austria;)

  • Stefan Thurner

    (a Section for the Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, A-1090 Vienna, Austria;; b Complexity Science Hub, A-1090 Vienna, Austria;; c Santa Fe Institute, Santa Fe, NM 87501)

Abstract

Social stability is often associated with triangular interactions between people. Various possible social triangles appear in peculiar ratios. The triangles “The friend of my friend is my friend” and “The enemy of my friend is my enemy” are strongly overrepresented, which plays an important role for social balance. A standard explanation for these characteristic triangle fractions is that people consider triadic information before forming social relations. This assumption often contradicts everyday experience. We propose an explanation of the observed overrepresentations without individuals having to consider triangles. A society where individuals minimize their social stress self-organizes toward the empirically observed triangular structures. We demonstrate this with data from a society of computer game players, where triangle formation can be directly observed.

Suggested Citation

  • Tuan Minh Pham & Jan Korbel & Rudolf Hanel & Stefan Thurner, 2022. "Empirical social triad statistics can be explained with dyadic homophylic interactions," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(6), pages 2121103119-, February.
    • Handle: RePEc:nas:journl:v:119:y:2022:p:e2121103119
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    Cited by:

    1. Meng, Fanyuan & Zhu, Jiadong & Yao, Yuheng & Fenoaltea, Enrico Maria & Xie, Yubo & Yang, Pingle & Liu, Run-Ran & Zhang, Jianlin, 2023. "Disagreement and fragmentation in growing groups," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).

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