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Eliciting Informative Feedback: The Peer-Prediction Method

Author

Listed:
  • Nolan Miller

    () (Kennedy School of Government, Harvard University, Cambridge, Massachusetts 02138)

  • Paul Resnick

    () (School of Information, University of Michigan, Ann Arbor, Michigan 48109-1092)

  • Richard Zeckhauser

    () (Kennedy School of Government, Harvard University, Cambridge, Massachusetts 02138)

Abstract

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.

Suggested Citation

  • Nolan Miller & Paul Resnick & Richard Zeckhauser, 2005. "Eliciting Informative Feedback: The Peer-Prediction Method," Management Science, INFORMS, vol. 51(9), pages 1359-1373, September.
  • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:9:p:1359-1373
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    File URL: http://dx.doi.org/10.1287/mnsc.1050.0379
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. D. J. Johnstone, 2011. "Economic Interpretation of Probabilities Estimated by Maximum Likelihood or Score," Management Science, INFORMS, vol. 57(2), pages 308-314, February.
    2. Aperjis, Christina & Zeckhauser, Richard J. & Miao, Yali, 2014. "Variable temptations and black mark reputations," Games and Economic Behavior, Elsevier, vol. 87(C), pages 70-90.
    3. Alessandro Acquisti, 2014. "Inducing Customers to Try New Goods," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 131-146, March.
    4. Yannis Bakos & Chrysanthos Dellarocas, 2011. "Cooperation Without Enforcement? A Comparative Analysis of Litigation and Online Reputation as Quality Assurance Mechanisms," Management Science, INFORMS, vol. 57(11), pages 1944-1962, November.
    5. Cristiano Codagnone & Federico Biagi & Fabienne Abadie, 2016. "The Passions and the Interests: Unpacking the ‘Sharing Economy’," JRC Working Papers JRC101279, Joint Research Centre (Seville site).
    6. Peysakhovich, Alexander & Plagborg-Møller, Mikkel, 2012. "A note on proper scoring rules and risk aversion," Economics Letters, Elsevier, vol. 117(1), pages 357-361.
    7. Gary Bolton & Ben Greiner & Axel Ockenfels, 2013. "Engineering Trust: Reciprocity in the Production of Reputation Information," Management Science, INFORMS, vol. 59(2), pages 265-285, January.
    8. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    9. repec:spr:annopr:v:253:y:2017:i:1:d:10.1007_s10479-016-2341-y is not listed on IDEAS
    10. Weijia Dai & Ginger Z. Jin & Jungmin Lee & Michael Luca, 2012. "Aggregation of Consumer Ratings: An Application to Yelp.com," NBER Working Papers 18567, National Bureau of Economic Research, Inc.
    11. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    12. Benjamin Van Roy & Xiang Yan, 2009. "Manipulation Robustness of Collaborative Filtering Systems," Working Papers 09-21, NET Institute, revised Sep 2009.
    13. Osório, António (António Miguel), 2016. "Judgement and Ranking: Living with Hidden Bias," Working Papers 2072/267264, Universitat Rovira i Virgili, Department of Economics.
    14. Benjamin Van Roy & Xiang Yan, 2010. "Manipulation Robustness of Collaborative Filtering," Management Science, INFORMS, vol. 56(11), pages 1911-1929, November.

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