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Statistical physics of balance theory

Author

Listed:
  • Andres M Belaza
  • Kevin Hoefman
  • Jan Ryckebusch
  • Aaron Bramson
  • Milan van den Heuvel
  • Koen Schoors

Abstract

Triadic relationships are accepted to play a key role in the dynamics of social and political networks. Building on insights gleaned from balance theory in social network studies and from Boltzmann-Gibbs statistical physics, we propose a model to quantitatively capture the dynamics of the four types of triadic relationships in a network. Central to our model are the triads’ incidence rates and the idea that those can be modeled by assigning a specific triadic energy to each type of triadic relation. We emphasize the role of the degeneracy of the different triads and how it impacts the degree of frustration in the political network. In order to account for a persistent form of disorder in the formation of the triadic relationships, we introduce the systemic variable temperature. In order to learn about the dynamics and motives, we propose a generic Hamiltonian with three terms to model the triadic energies. One term is connected with a three-body interaction that captures balance theory. The other terms take into account the impact of heterogeneity and of negative edges in the triads. The validity of our model is tested on four datasets including the time series of triadic relationships for the standings between two classes of alliances in a massively multiplayer online game (MMOG). We also analyze real-world data for the relationships between the “agents” involved in the Syrian civil war, and in the relations between countries during the Cold War era. We find emerging properties in the triadic relationships in a political network, for example reflecting itself in a persistent hierarchy between the four triadic energies, and in the consistency of the extracted parameters from comparing the model Hamiltonian to the data.

Suggested Citation

  • Andres M Belaza & Kevin Hoefman & Jan Ryckebusch & Aaron Bramson & Milan van den Heuvel & Koen Schoors, 2017. "Statistical physics of balance theory," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-19, August.
  • Handle: RePEc:plo:pone00:0183696
    DOI: 10.1371/journal.pone.0183696
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    Citations

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    Cited by:

    1. Sheykhali, Somaye & Darooneh, Amir Hossein & Jafari, Gholam Reza, 2020. "Partial balance in social networks with stubborn links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    2. Arabzadeh, S. & Sherafati, M. & Atyabi, F. & Jafari, G.R. & Kułakowski, K., 2021. "Lifetime of links influences the evolution towards structural balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    3. Andres M Belaza & Jan Ryckebusch & Koen Schoors & Luis E C Rocha & Benjamin Vandermarliere, 2020. "On the connection between real-world circumstances and online player behaviour: The case of EVE Online," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-15, October.

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