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Visual influence networks in walking crowds.

Kei Yoshida1, Mario di Bernardo2,3, William H Warren1

  • 1Department of Cognitive and Psychological Sciences, Brown University, Providence, RI, USA.

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Summary
This summary is machine-generated.

Researchers mapped human crowd influence networks using visual interactions. Front-positioned individuals show greater global leadership, explaining how small groups influence large crowds and informing crowd management.

Keywords:
collective behaviourcrowd dynamicsleadershipnetwork analysispedestrian dynamics

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Area of Science:

  • Social dynamics
  • Network science
  • Human behavior

Background:

  • Collective motion in animal groups is understood through visual interactions.
  • The network structure of human crowd dynamics is not well-understood.
  • Previous research has not explored dynamic visual influence networks in human crowds.

Purpose of the Study:

  • To develop a method for reconstructing dynamic visual influence networks in human crowds.
  • To introduce new network measures for quantifying leadership in crowds.
  • To investigate the spatial gradients of influence within human crowds.

Main Methods:

  • Reconstruction of dynamic visual influence networks using motion-capture data.
  • Application of time-dependent delayed directional correlation with visibility constraints (visual field size, occlusion).
  • Introduction of direct influence (local leadership) and branching influence (global leadership) network measures.

Main Results:

  • Distinct spatial gradients in direct and branching influence were revealed.
  • Front-positioned individuals demonstrated greater global influence than rear-positioned individuals.
  • Individual spatial position significantly explained leadership variance within the crowd.

Conclusions:

  • A small number of individuals can significantly influence the motion of large human crowds.
  • Quantitative principles for crowd networks, paralleling animal flock leadership, were established.
  • Findings provide evidence-based foundations for effective human crowd management strategies.