AAAI Publications, Fifth AAAI Conference on Human Computation and Crowdsourcing

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Effective Prize Structure for Simple Crowdsourcing Contests with Participation Costs
David Sarne, Michael Lepioshkin

Last modified: 2017-09-21

Abstract


This paper studies the use of a multi-prize compensation scheme for "simple" contests where participation is costly and the quality of participants' contributions is a priori uncertain at the time they make their decision related to participating in the contest. The equilibrium analysis provided enables demonstrating not only that a multi-prize structure is often beneficial but also that in some cases the principal's expected profit is maximized when offering a second prize greater than the first prize. This may seem somehow counter-intuitive especially given that the principal's profit is only influenced by the quality of the best submission rather than the aggregate of submissions. Special emphasis is placed on the case where the contestants are a priori homogeneous which is often the case in real-life, whenever the contestants are basically a priori alike and the quality of their submissions is determined subjectively by some referee. Here, we manage to prove that a multi-prize structure is dominated by a winner-takes-all scheme, suggesting that the benefit in the multi-prize contest scheme fully derives from the heterogeneity between prospective contestants. Finally, we show that there is a class of settings where the use of the multi-prize crowdsourcing contest model enables achieving the performance of the fully cooperative model (which is an upper bound for the performance in any type of contest), and that for settings of this class the optimal prize allocation can be extracted through a set of linear equations.

Keywords


Crowdsourcing; Contest Design; Prize Allocation

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