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American Economic Journal: Microeconomics: Vol. 2 No. 1 (February 2010)

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Naïve Learning in Social Networks and the Wisdom of Crowds

Article Citation

Golub, Benjamin, and Matthew O. Jackson. 2010. "Naïve Learning in Social Networks and the Wisdom of Crowds." American Economic Journal: Microeconomics, 2(1): 112-49.

DOI: 10.1257/mic.2.1.112

Abstract

We study learning in a setting where agents receive independent noisy signals about the true value of a variable and then communicate in a network. They naïvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. We show that all opinions in a large society converge to the truth if and only if the influence of the most influential agent vanishes as the society grows. We also identify obstructions to this, including prominent groups, and provide structural conditions on the network ensuring efficient learning. Whether agents converge to the truth is unrelated to how quickly consensus is approached. (JEL D83, D85, Z13)

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Authors

Golub, Benjamin (Stanford U)
Jackson, Matthew O. (Stanford U and Santa Fe Institute)

JEL Classifications

D83: Search; Learning; Information and Knowledge; Communication; Belief
D85: Network Formation and Analysis: Theory
Z13: Economic Sociology; Economic Anthropology; Social and Economic Stratification

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American Economic Journal: Microeconomics


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