Identifying Social Influence in Networks Using Randomized Experiments

IEEE Intelligent Systems, Forthcoming

12 Pages Posted: 11 Aug 2011  

Sinan Aral

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Dylan Walker

Boston University

Date Written: August 10, 2011

Abstract

Identifying causal estimates of peer-to-peer influence in networks is critical to marketing strategy, public policy and beyond. Unfortunately, separating correlation from causation in networked data is complicated. We argue that randomized experimentation in networks, made possible by the digitization of human interaction at population scale, can dramatically improve our understanding of the ebb and flow of market trends, product adoption and diffusion, the spread of health behaviors, the productivity of information workers and whether or not particular individuals in a social network have a disproportionate amount of influence on the system. We also discuss some of the complications that arise when conducting randomized experiments in networks by describing an experiment designed to test how different viral product design strategies affect peer influence and social contagion in new product diffusion.

Keywords: Peer Influence, Social Contagion, Social Networks, Endogeneity, Causality, Randomized Experiments

Suggested Citation

Aral, Sinan and Walker, Dylan, Identifying Social Influence in Networks Using Randomized Experiments (August 10, 2011). IEEE Intelligent Systems, Forthcoming. Available at SSRN: https://ssrn.com/abstract=1907785

Sinan Aral (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

77 Massachusetts Ave.
E62-416
Cambridge, MA 02142
United States

Dylan Walker

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

HOME PAGE: http://www.dylantwalker.com

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