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	Provedor de dados AgEcon (2) Autor Golub, Benjamin (2) Jackson, Matthew O. (2) Palavra-chave D83 (2) D85 (2) Diffusion (2) Institutional and Behavioral Economics (2) Learning (2) Social Networks (2) Z13 (2) A14 (1) Bounded Rationality (1) Convergence (1) Friendships (1) Homophily (1) I21 (1) J15 (1) L14 (1) Mixing Time (1) Networks (1) Random Graphs (1) Speed of Convergence (1) Speed of Learning (1) Mais... Tipo do documento Working or Discussion Paper (2) Ano 2009 (1) 2007 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Naive Learning in Social Networks: Convergence, Influence and Wisdom of Crowds AgEcon Jackson, Matthew O.; Golub, Benjamin; Jackson, Matthew O.. We study learning and influence in a setting where agents communicate according to an arbitrary social network and naively update their beliefs by repeatedly taking weighted averages of their neighbors' opinions. A focus is on conditions under which beliefs of all agents in large societies converge to the truth, despite their naive updating. We show that this happens if and only if the influence of the most influential agent in the society is vanishing as the society grows. Using simple examples, we identify two main obstructions which can prevent this. By ruling out these obstructions, we provide general structural conditions on the social network that are sufficient for convergence to truth. In addition, we show how social influence changes when some... Tipo: Working or Discussion Paper Palavras-chave: Social Networks; Learning; Diffusion; Bounded Rationality; Institutional and Behavioral Economics; D85; D83; A14; L14; Z13. Ano: 2007 URL: http://purl.umn.edu/9101 How Homophily Affects Learning and Diffusion in Networks AgEcon Golub, Benjamin; Jackson, Matthew O.. We examine how three different communication processes operating through social networks are affected by homophily - the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are broadcast or sent via shortest paths; only connection density matters. In contrast, homophily substantially slows learning based on repeated averaging of neighbors' information and Markovian diffusion processes such as the Google random surfer model. Indeed, the latter processes are strongly affected by homophily but completely independent of connection density, provided this density exceeds a low threshold. We obtain these results by establishing new results on the spectra of large random graphs and relating the spectra to... Tipo: Working or Discussion Paper Palavras-chave: Networks; Learning; Diffusion; Homophily; Friendships; Social Networks; Random Graphs; Mixing Time; Convergence; Speed of Learning; Speed of Convergence; Institutional and Behavioral Economics; D83; D85; I21; J15; Z13. Ano: 2009 URL: http://purl.umn.edu/50718 Registros recuperados: 2 Primeira ... 1 ... Última

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