Social Learning in Social Networks
P. J. Lamberson
Northwestern University - Department of Management & Organizations; Northwestern Institute on Complex Systems (NICO)
November 3, 2009
MIT Sloan Research Paper No. 4763-09
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.
Number of Pages in PDF File: 33
Keywords: social networks, learning, diffusion, mean-ﬁeld analysis, stochastic dominanceworking papers series
Date posted: November 4, 2009
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