title: Rapid innovation diffusion in social networks.
abstract: Social and technological innovations often spread through social networks as people respond to what their neighbors are doing. Previous research has identified specific network structures, such as local clustering, that promote rapid diffusion. Here we derive bounds that are independent of network structure and size, such that diffusion is fast whenever the payoff gain from the innovation is sufficiently high and the agents' responses are sufficiently noisy. We also provide a simple method for computing an upper bound on the expected time it takes for the innovation to become established in any finite network. For example, if agents choose log-linear responses to what their neighbors are doing, it takes on average less than 80 revision periods for the innovation to diffuse widely in any network, provided that the error rate is at least 5% and the payoff gain (relative to the status quo) is at least 150%. Qualitatively similar results hold for other smoothed best-response functions and populations that experience heterogeneous payoff shocks.
authors.affiliation: Department of Economics, Massachusetts Institute of Technology, Cambridge, MA 02139; gek@mit.edu.
authors.forename: Gabriel E
authors.initials: GE
authors.lastname: Kreindler
authors.affiliation: Department of Economics, University of Oxford, Oxford OX1 3UQ, United Kingdom; andThe Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, Oxford OX1 3BD, United Kingdom.
authors.forename: H Peyton
authors.initials: HP
authors.lastname: Young
mesh_terms: D019058:Community Networks; D003198:Computer Simulation; D004059:Diffusion of Innovation; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D008962:Models, Theoretical; D012944:Social Support; D013269:Stochastic Processes; D013997:Time Factors
keywords: convergence time; coordination game; local interaction model; logit; noisy best response