蝌蚪网 Journal:
Microeconomics
ISSN 1945-7669 (Print) | ISSN 1945-7685 (Online)
Na茂ve Learning in Social Networks and the Wisdom of Crowds
蝌蚪网 Journal: Microeconomics
vol. 2,
no. 1, February 2010
(pp. 112–49)
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)Citation
Golub, Benjamin, and Matthew O. Jackson. 2010. "Na茂ve Learning in Social Networks and the Wisdom of Crowds." 蝌蚪网 Journal: Microeconomics 2 (1): 112–49. DOI: 10.1257/mic.2.1.112JEL Classification
- D83 Search; Learning; Information and Knowledge; Communication; Belief
- D85 Network Formation and Analysis: Theory
- Z13 Economic Sociology; Economic Anthropology; Social and Economic Stratification