Identifying Influential and Susceptible Members of Social Networks
Who Influences Who?
A goal in social science is how to assess people's influence over one. Aral and Walker (p. 337, published online 21 June) describe a generalized method for identifying influential and susceptible members of social networks based on large-scale in vivo randomized experimentation. The method was used to estimate peer effects in consumer demand for a commercial Facebook application in a representative sample of 12 million Facebook users. Older users were more influential than younger users, women were more influential over men than men over women, and married individuals were the least susceptible to influence in the decision to adopt the product studied.
Abstract
Identifying social influence in networks is critical to understanding how behaviors spread. We present a method that uses in vivo randomized experimentation to identify influence and susceptibility in networks while avoiding the biases inherent in traditional estimates of social contagion. Estimation in a representative sample of 1.3 million Facebook users showed that younger users are more susceptible to influence than older users, men are more influential than women, women influence men more than they influence other women, and married individuals are the least susceptible to influence in the decision to adopt the product offered. Analysis of influence and susceptibility together with network structure revealed that influential individuals are less susceptible to influence than noninfluential individuals and that they cluster in the network while susceptible individuals do not, which suggests that influential people with influential friends may be instrumental in the spread of this product in the network.
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Supplementary Material
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Materials and Methods
Figs. S1 to S12
Tables S1 to S9
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References and Notes
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Published In
Science
Volume 337 | Issue 6092
20 July 2012
20 July 2012
Copyright
Copyright © 2012, American Association for the Advancement of Science.
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Submission history
Received: 26 October 2011
Accepted: 30 May 2012
Published in print: 20 July 2012
Acknowledgments
We thank S. Aral, H. Frydman, C. Hurvich, P. Perry, J. Simonoff, and M. Sternberg for invaluable discussions. Supported by a Microsoft research faculty fellowship (S.A.) and by NSF Career Award 0953832 (S.A.). The research was approved by the NYU institutional review board. There are legal obstacles to making the data available, but code is available upon request. The requests for data and randomization of message targets we used are standard ways in which applications request and use user data on Facebook. They are covered by the Facebook privacy policy and terms of service. Opt-in permissions were granted by the user to the application developer on a per-application basis when the user installed the application, via Facebook application authentication dialogs. In the dialogs we asked for all the categories of data we used in the study, and all of these requests were in line with the Facebook terms of service. Users saw these requests and opted in to them before installing the app.
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- Sinan Aral,
- Dylan Walker
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