Eliciting informative feedback: The peer-prediction method

• 成果类型: Article
• 署名作者: Miller, N; Resnick, P; Zeckhauser, R
• 署名单位: Harvard University; University of Michigan System; University of Michigan
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.1050.0379
• 发表日期: 2005
• 页码: 1359-1373
• 关键词: proper scoring rules; electronic markets; honest feedback

摘要

Many recommendation and decision processes depend on eliciting evaluations of opportunities, products, and vendors. A scoring system is devised that induces honest reporting of feedback. Each rater merely reports a signal, and the system applies proper scoring rules to the implied posterior beliefs about another rater's report. Honest reporting proves to be a Nash equilibrium. The scoring schemes can be scaled to induce appropriate effort by raters and can be extended to handle sequential interaction and continuous signals. We also address a number of practical implementation issues that arise in settings such as academic reviewing and online recommender and reputation systems.