Strategyproofing Peer Assessment via Partitioning: The Price in Terms of Evaluators’ Expertise

Strategic behavior is a fundamental problem in a variety of real-world applications that require some form of peer assessment, such as peer grading of home works, grant proposal review, conference peer review of scientific papers, and peer assessment of employees in organizations. Since an individual’ sown work is in competition with the submissions the yare evaluating, they may provide dishonest evaluations to increase the relative standing of their own submission. This issue is typically addressed by partitioning the individuals and assigning them to evaluate the work of only those from different subsets. Although this method ensures strategy proofness, each submission may require a different type of expertise for effective evaluation. In this paper, we focus on finding an assignment of evaluators to submissions that maximizes assigned evaluators’ expertise subject to the constraint of strategy proofness. We analyze the price of strategy proofness: that is, the amount of compromise on the assigned evaluators’ expertise required in order to get strategy proofness. We establishesveral polynomial-time algorithms for strategy proof assignment long with assignment-quality guarantees. Finally, we evaluate the methods on a dataset from conference peer review.