Information Inundation on Platforms and Implications

• 成果类型: Article
• 署名作者: Allon, Gad; Drakopoulos, Kimon; Manshadi, Vahideh
• 署名单位: University of Pennsylvania; University of Southern California; Yale University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2021.2119
• 发表日期: 2021
• 页码: 1784-1804
• 关键词: information platforms; Bayesian learning; opinion dynamics; polarization

摘要

In this paper, we study a model of information consumption in which consumers sequentially interact with a platform that offers a menu of signals (posts) about an underlying state of the world (fact). At each time, incapable of consuming all posts, consumers screen the posts and only select (and consume) one from the offered menu. We show that, in the presence of uncertainty about the accuracy of these posts and as the number of posts increases, adverse effects, such as slow learning and polarization, arise. Specifically, we establish that, in this setting, bias emerges as a consequence of the consumer's screening process. Namely, consumers, in their quest to choose the post that reduces their uncertainty about the state of the world, choose to consume the post that is closest to their own beliefs. We study the evolution of beliefs, and we show that such a screening bias slows down the learning process and that the speed of learning decreases with the menu size. Further, we show that the society becomes polarized during the prolonged learning process even in situations in which the society's belief distribution was not a priori polarized.