Preferences, Homophily, and Social Learning

Ilan Lobel () and Evan Sadler ()
Additional contact information
Ilan Lobel: Stern School of Business, New York University, New York, New York 10012
Evan Sadler: Stern School of Business, New York University, New York, New York 10012

Operations Research, 2016, vol. 64, issue 3, 564-584

Abstract: We study a sequential model of Bayesian social learning in networks in which agents have heterogeneous preferences, and neighbors tend to have similar preferences—a phenomenon known as homophily. We find that the density of network connections determines the impact of preference diversity and homophily on learning. When connections are sparse, diverse preferences are harmful to learning, and homophily may lead to substantial improvements. In contrast, in a dense network, preference diversity is beneficial. Intuitively, diverse ties introduce more independence between observations while providing less information individually. Homophilous connections individually carry more useful information, but multiple observations become redundant.

Keywords: network/graphs; probability; games/group decisions (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.2015.1364 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:64:y:2016:i:3:p:564-584

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().