Distilling the Wisdom of Crowds: Prediction Markets vs. Prediction Polls

• 成果类型: Article
• 署名作者: Atanasov, Pavel; Rescober, Phillip; Stone, Eric; Swift, Samuel A.; Servan-Schreiber, Emile; Tetlock, Philip; Ungar, Lyle; Mellers, Barbara
• 署名单位: University of Pennsylvania; University of Pennsylvania; University of Pennsylvania
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2015.2374
• 发表日期: 2017
• 页码: 691-706
• 关键词: Forecasting; prediction markets; crowdsourcing; belief elicitation

摘要

We report the results of the first large-scale, long-term, experimental test between two crowdsourcing methods: prediction markets and prediction polls. More than 2,400 participants made forecasts on 261 events over two seasons of a geopolitical prediction tournament. Forecasters were randomly assigned to either prediction markets (continuous double auction markets) in which theywere ranked based on earnings, or prediction polls in which they submitted probability judgments, independently or in teams, and were ranked based on Brier scores. In both seasons of the tournament, prices from the prediction market were more accurate than the simple mean of forecasts from prediction polls. However, team prediction polls outperformed prediction markets when forecasts were statistically aggregated using temporal decay, differential weighting based on past performance, and recalibration. The biggest advantage of prediction pollswas at the beginning of long-duration questions. Results suggest that prediction polls with proper scoring feedback, collaboration features, and statistical aggregation are an attractive alternative to prediction markets for distilling the wisdom of crowds.