The Crowd Machine: Leveraging Emergent Crowd Behavior in Policy and Response

Abstract

All across the country, officials and planners of the first-responder community plan for events of various types, yet their plans do not adequately account for crowd behavior when the event is interrupted by an act of violence that turns into a mass-casualty incident, or a "focus event." This research contests early crowd psychology studies and presents the contemporary social identity theory, elaborated social identity model, and emergence model as better lenses for crowd behavior in responding to a focus event. Case studies of the 2013 Boston Marathon bombing and the 2017 Las Vegas mass shooting are used to analyze crowds that experienced focus events through the perspective of complex adaptive systems. A new framework that incorporates the elements of stress, panic, chaos, and priming is then presented to assist officials and planners with planning for crowds experiencing a focus event, with the aim of leveraging crowd emergence. The new framework presented in this research leads to a set of actionable recommendations for policymakers and planners. Ultimately, this thesis challenges officials and planners of the first-responder community to evaluate crowds as complex adaptive systems and explore the ability to leverage crowds for a more effective response.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1150455

Entities

People

  • Craig M. Cooper

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Adaptive Systems
  • Command And Control
  • Complex Adaptive Systems
  • Department Of Homeland Security
  • Emergency Response
  • First Responders
  • Group Dynamics
  • Health Services
  • Homeland Security
  • Human Behavior
  • Law Enforcement Officers
  • Medical Personnel
  • Personnel Management
  • Psychology
  • Self Organizing Systems
  • Social Psychology
  • Societies

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Emergency Management and Homeland Security.
  • Systems Analysis and Design