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From equality to diversity: A bottom-up approach for hierarchy growth

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  • Czaplicka, Agnieszka
  • Hołyst, Janusz A.

Abstract

Hierarchical topology stands as a fundamental property of many complex systems. In this work, we present a simple yet insightful model that captures hierarchy growth from bottom to top. Our model incorporates two key dynamic processes: the emergence of local leaders through promotions, where successful agents advance to higher hierarchical levels by attracting followers, and the natural degradation of agents to the lowest level. From an initial flat structure where all agents occupy the bottom level, the system evolves toward a stationary state characterized by an exponential distribution of agents across levels—a pattern remarkably similar to those observed in diverse real-world hierarchies, from hunter-gatherer societies and mammalian groups to online communities. Notably, while the average hierarchy level and the fraction of ground-level agents remain independent of system size, the maximum height of the hierarchy grows logarithmically with the total number of agents. In the stationary state, agents maintain a significantly smaller number of followers compared to their peak influence at the promotion moment. Results from numerical simulations are supported by analytical solutions derived based on the rate equations.

Suggested Citation

  • Czaplicka, Agnieszka & Hołyst, Janusz A., 2026. "From equality to diversity: A bottom-up approach for hierarchy growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 681(C).
  • Handle: RePEc:eee:phsmap:v:681:y:2026:i:c:s0378437125007149
    DOI: 10.1016/j.physa.2025.131062
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    1. repec:plo:pone00:0033799 is not listed on IDEAS
    2. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    3. Tamás Nepusz & Tamás Vicsek, 2013. "Hierarchical Self-Organization of Non-Cooperating Individuals," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-9, December.
    4. H. Jeong & S. P. Mason & A.-L. Barabási & Z. N. Oltvai, 2001. "Lethality and centrality in protein networks," Nature, Nature, vol. 411(6833), pages 41-42, May.
    5. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    6. K. Malarz & D. Stauffer & K. Kułakowski, 2006. "Bonabeau model on a fully connected graph," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 195-198, March.
    7. Hołyst, Janusz A. & Kacperski, Krzysztof & Schweitzer, Frank, 2000. "Phase transitions in social impact models of opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 199-210.
    8. Kacperski, Krzysztof & Hoł yst, Janusz A., 1999. "Opinion formation model with strong leader and external impact: a mean field approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(2), pages 511-526.
    9. Emily Webber & Robin Dunbar, 2020. "The fractal structure of communities of practice: Implications for business organization," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-15, April.
    10. Dietrich Stauffer, 2003. "Phase Transition In Hierarchy Model Of Bonabeau," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(02), pages 237-239.
    11. Bonabeau, Eric & Theraulaz, Guy & Deneubourg, Jean-Louis, 1995. "Phase diagram of a model of self-organizing hierarchies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 217(3), pages 373-392.
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