A game-theoretic analysis of rank-order mechanisms for user-generated content

• 成果类型: Article
• 署名作者: Ghosh, Arpita; Hummel, Patrick
• 署名单位: Cornell University; Alphabet Inc.; Google Incorporated
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2014.09.009
• 发表日期: 2014
• 页码: 349-374
• 关键词: Attention economics; game theory; Rank-order mechanisms; user-generated content

摘要

We investigate the widely-used rank-order mechanism for displaying user-generated content, where contributions are displayed on a webpage in decreasing order of their ratings, in a game-theoretic model where strategic contributors benefit from attention and have a cost to quality. We show that the lowest quality elicited by this rank-order mechanism in any mixed-strategy equilibrium becomes optimal as the available attention diverges. Additionally, these equilibrium qualities are higher, with probability tending to 1 in the limit of diverging attention, than those elicited by a more equitable proportional mechanism which distributes attention in proportion to the positive ratings a contribution receives, but the proportional mechanism elicits a greater number of contributions than the rank-order mechanism. (c) 2014 Elsevier Inc. All rights reserved.