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The HoneyComb Paradigm for Research on Collective Human Behavior
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Collective behavior.

Robert L Goldstone1, Todd M Gureckis

  • 1Indiana University, BloomingtonNew York University.

Topics in Cognitive Science
|August 29, 2014
PubMed
Summary
This summary is machine-generated.

Collective behavior studies benefit from new tools in experimentation, data analysis, and computational modeling. This research framework analyzes group dynamics across diverse collectives, from bee swarms to online communities.

Keywords:
Collective behaviorComputational modelsGroup psychologyInnovation diffusion

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Area of Science:

  • Social Psychology
  • Computational Social Science
  • Behavioral Economics

Background:

  • Resurgent interest in collective behavior driven by new research tools.
  • Growth of online self-organized collectives and computational modeling methods.
  • Need for frameworks to analyze diverse group patterns.

Purpose of the Study:

  • To present a framework for analyzing collective behavior.
  • To compare collective patterns across various case studies.
  • To review critical issues in understanding group dynamics.

Main Methods:

  • Case study analysis of collective behavior attributes: motivation, interaction, dynamics, and outcomes.
  • Comparison of diverse groups: noninteracting decision makers, bee swarms, path formation, sports teams, resource competition, and online innovation spread.
  • Review of key theoretical questions in collective behavior.

Main Results:

  • A comparative framework is established for understanding collective behavior.
  • Diverse collective phenomena can be analyzed using consistent attributes.
  • Identified commonalities and differences in group dynamics and outcomes across varied contexts.

Conclusions:

  • Collective behavior is a complex phenomenon not always reducible to individual actions.
  • The possibility and nature of 'group cognition' remain open questions.
  • Formal modeling offers valuable insights into understanding group behavior and social patterns.