Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2018-02-28
Number: 18-018/II
Author-Name: Bernd (B.) Heidergott
Author-Email: b.f.heidergott@vu.nl
Author-Workplace-Name: VU Amsterdam, The Netherlands
Author-Name: Jia-Ping Huang
Author-Email: huangjp28@sina.com
Author-Workplace-Name: Shenzhen University, China
Author-Name: Ines (I.) Lindner
Author-Email: i.d.lindner@vu.nl
Author-Workplace-Name: VU Amsterdam, The Netherlands
Title: Naive Learning in Social Networks with Random Communication
Abstract: We study social learning in a social network setting where agents receive independent noisy signals about the truth. Agents naïvely update beliefs by repeatedly taking weighted averages of neighbors' opinions. The weights are fixed in the sense of representing average frequency and intensity of social interaction. However, the way people communicate is random such that agents do not update their belief in exactly the same way at every point in time. We show that even if the social network does not privilege any agent in terms of influence, a large society almost always fails to converge to the truth.   We conclude that wisdom of crowds is an illusive concept and bares the danger of mistaking consensus for truth.
Classification-JEL: D83, D85, C63
Keywords: Wisdom of crowds, social networks, information cascades, naive learning
File-Url: https://papers.tinbergen.nl/18018.pdf
File-Format: application/pdf
File-Size: 992914 bytes
Handle: RePEc:tin:wpaper:20180018