Social Learning in Social Networks

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, we prove that the diffusion process always has at least one stable equilibrium, and we examine the dependance of the set of equilibria on the model parameters and the structure of the network. In particular, we show how first and second order stochastic dominance shifts in the degree distribution of the network impact diffusion. We 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 we derive the precise conditions characterizing those relationships.

When knowledgeable neighbors also share seedlings: diffusion of banana cultivation in Tanzania

“…I assume that the variance of the belief is inversely related to the number of informants, N , weighted by the quality of their information, q . This assumption can be motivated by a Bayesian updating model typically employed in the social learning literature (Acemoglu et al., ; Foster and Rosenzweig, ; Lamberson, ; Munshi, ), where the variance of the signals from each informant is and the variance of the prior is . When the farmer has no informants the variance of the belief is .…”

A Mecânica da Desinformação em Redes Epistêmicas e as Contribuições da Filosofia da Ciência de Susan Haack

“…É muito prevalente na cultura ocidental uma epistemologia racionalista que entende que os seres humanos podem obter conhecimento verdadeiro e tomar decisões perfeitas se tão somente guiarem seus raciocínios por meio da lógica e de uma análise racional de todas as variáveis envolvidas, e que as falhas em fazê-lo decorrem de falhas no emprego dessa racionalidade inata ao homem (Lamberson, 2010), resultando, por exemplo, de tiques psicológicos ou vieses cognitivos (Dawson;Gilovich;Regan, 2002). Nessa perspectiva, para se melhorar a aquisição informativa de uma comunidade epistêmica, é preciso apenas trabalhar a capacidade de raciocínio dos indivíduos.…”

Diffusion of Cooperative Behavior in Decentralized Cognitive Radio Networks With Selfish Spectrum Sensors

“…The analytical complexity is further reduced by assuming that at each time instant the neighbors of each ICR are drawn randomly from the population. Therefore, the network degree distribution P (d) can be used to characterize the diffusion process instead of having to account for all possible network connections and topologies, which is nearly intractable [30], [36], [43].…”