Abstract

http://ssrn.com/abstract=1770982
 
 

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Engineering Social Contagions: Optimal Network Seeding in the Presence of Homophily


Sinan Aral


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

Lev Muchnik


Independent

Arun Sundararajan


New York University (NYU) - Leonard N. Stern School of Business

February 18, 2013

Forthcoming in Network Science

Abstract:     
We use data on a real, large-scale social network of 27 million individuals interacting daily, together with the day-by-day adoption of a new mobile service product, to inform, build and analyze data-driven simulations of the effectiveness of seeding (network targeting) strategies under different social conditions. Three main results emerge from our simulations. First, failure to consider homophily creates significant overestimation of the effectiveness of seeding strategies, casting doubt on conclusions drawn by simulation studies that do not model homophily. Second, seeding is constrained by the small fraction of potential influencers that exist in the network. We find that seeding more than 0.2% of the population is wasteful because the gain from their adoption is lower than the gain from their natural adoption (without seeding). Third, seeding is more effective in the presence of greater social influence. Stronger peer influence creates a greater than additive effect when combined with seeding. Our findings call into question some conventional wisdom about these strategies and suggest that their overall effectiveness may be overestimated.

Number of Pages in PDF File: 44

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Date posted: February 27, 2011 ; Last revised: February 20, 2013

Suggested Citation

Aral, Sinan and Muchnik, Lev and Sundararajan, Arun, Engineering Social Contagions: Optimal Network Seeding in the Presence of Homophily (February 18, 2013). Forthcoming in Network Science. Available at SSRN: http://ssrn.com/abstract=1770982 or http://dx.doi.org/10.2139/ssrn.1770982

Contact Information

Sinan Aral (Contact Author)
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
77 Massachusetts Ave.
E62-416
Cambridge, MA 02142
United States
Lev Muchnik
Independent ( email )
No Address Available
United States
Arun Sundararajan
New York University (NYU) - Leonard N. Stern School of Business ( email )
44 West 4th Street, KMC 8-93
New York, NY 10012
United States
212-998-0833 (Phone)
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