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The HoneyComb Paradigm for Research on Collective Human Behavior
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A hypernetwork-based urn model for explaining collective dynamics.

Jiali Lu1, Haifeng Du1, Xiaochen He1,2

  • 1School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, Shaanxi Province, China.

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|September 19, 2023
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Summary
This summary is machine-generated.

This study introduces a hypernetwork-based Pólya urn model to explain collective dynamics, finding that social influence can hinder self-correction and increase unpredictability in social systems.

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Area of Science:

  • Complex Systems Science
  • Network Theory
  • Social Dynamics

Background:

  • Topological characterization of complex systems aids understanding collective dynamics.
  • General complex network representations are insufficient for explaining phenomena like collective actions.
  • Hypernetworks offer effective modeling for real-world complex networks.

Purpose of the Study:

  • To propose a novel hypernetwork-based Pólya urn model.
  • To incorporate the effect of group identity into collective dynamics modeling.
  • To analyze the impact of social influence and group identity on social systems.

Main Methods:

  • Developed a hypernetwork-based Pólya urn model.
  • Employed mathematical deduction for theoretical analysis.
  • Conducted simulation experiments to validate findings.

Main Results:

  • Social influence creates an imitation environment, preventing self-correction in dynamics.
  • System unpredictability escalates with increased social influence.
  • Group identity moderates market inequality arising from individual preferences and social influence.

Conclusions:

  • The proposed model provides a basis for understanding collective dynamics logic.
  • Social influence and group identity are critical factors in social system behavior.
  • Hypernetwork modeling offers a powerful framework for complex social phenomena.