Manipulation-Resistant Reputation Systems

Friedman, Eric, Resnick, Paul, and Sami, Rahul. “Manipulation-Resistant Reputation Systems”. Chapter 27 in Algorithmic Game Theory. Edited by Noam Nisan, Tim Roughgarden, Eva Tardos, and Vijay Vazirani. Cambridge University Press. 2007.

Please email me to get a copy of the paper.


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 raters report. Honest reporting proves to be a Nash Equilibrium. The scoring schemes can be scaled to induce appropriate e¤ort 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 on-line recommender and reputation systems.