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Social Learning in Social Networks

Author(s)
Lamberson, PJ
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Abstract
This paper analyzes a model of social learning in a social network. Agents decide whether or not to adopt a new technology with unknown payoffs based on their prior beliefs and the experiences of their neighbors in the network. Using a mean-field approximation, I prove that the diffusion process always has at least one stable equilibrium, and I examine the dependence of the set of equilibria on the model parameters and the structure of the network. In particular, I show how first and second order stochastic dominance shifts in the degree distribution of the network impact diffusion. I find that the relationship between equilibrium diffusion levels and network structure depends on the distribution of payoffs to adoption and the distribution of agents' prior beliefs regarding those payoffs, and I derive the precise conditions characterizing those relationships.
Date issued
2009-10
URI
http://hdl.handle.net/1721.1/66569
Publisher
Cambridge, MA; Alfred P. Sloan School of Management, Massachusetts Institute of Technology
Series/Report no.
MIT Sloan School of Management Working Paper;4763-09
Keywords
social networks, diffusion, mean-field analysis, stochastic dominance

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