Citations (2)



Identifying Social Influence in Networks Using Randomized Experiments

Sinan Aral

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

Dylan Walker

Boston University

August 10, 2011

IEEE Intelligent Systems, Forthcoming

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.

Number of Pages in PDF File: 12

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

Accepted Paper Series

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Date posted: August 11, 2011  

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: http://ssrn.com/abstract=1907785

Contact Information

Sinan Aral (Contact Author)
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
77 Massachusetts Ave.
Cambridge, MA 02142
United States
Dylan Walker
Boston University ( email )
595 Commonwealth Avenue
Boston, MA 02215
United States
HOME PAGE: http://www.dylantwalker.com
Feedback to SSRN

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