Preferences, Homophily, and Social Learning

• 成果类型: Article
• 署名作者: Lobel, Ilan; Sadler, Evan
• 署名单位: New York University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2015.1364
• 发表日期: 2016
• 页码: 564-584
• 关键词: WEAK TIES; networks; INFORMATION; DYNAMICS; BEHAVIOR; CHOICE; speed; MODEL

摘要

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.