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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
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