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Statistics in Medicine· 2012Q1· Review

Social contagion theory: examining dynamic social networks and human behavior

Nicholas A. Christakis, James H. Fowler

Short summary

Human social networks exhibit a 'three degrees of influence' property, affecting behaviors like obesity, smoking, cooperation, and happiness.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Human social networks may exhibit a 'three degrees of influence' property.
  • Social contagion influences diverse behaviors including obesity, smoking, cooperation, and happiness.
  • Research utilizes datasets such as the Framingham Heart Study and the National Longitudinal Study of Adolescent Health.
  • Current methods for causal inference in social network data have limitations, with ongoing development needed.

AI-generated from the title and abstract; the full text is not read.

Abstract

Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a 'three degrees of influence' property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations.

The authors' abstract, as published at the source. Statistics in Medicine, 2012 · DOI ↗

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Field: Statistical and Nonlinear Physics

Statistical and Nonlinear PhysicsPhysics and Astronomy