33 Pages Posted: 4 Nov 2009
Date Written: November 3, 2009
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.
Keywords: social networks, learning, diffusion, mean-ﬁeld analysis, stochastic dominance
Suggested Citation: Suggested Citation
Lamberson, PJ, Social Learning in Social Networks (November 3, 2009). MIT Sloan Research Paper No. 4763-09. Available at SSRN: https://ssrn.com/abstract=1499424 or http://dx.doi.org/10.2139/ssrn.1499424