%0 Generic %1 Chawla2011 %A Chawla, Shuchi %A Hartline, Jason D. %A Sivan, Balasubramanian %D 2011 %K citizenscience crowdsourcing %T Optimal Crowdsourcing Contests %U http://arxiv.org/abs/1111.2893 %X We study the design and approximation of optimal crowdsourcing contests. Crowdsourcing contests can be modeled as all-pay auctions because entrants must exert effort up-front to enter. Unlike all-pay auctions where a usual design objective would be to maximize revenue, in crowdsourcing contests, the principal only benefits from the submission with the highest quality. We give a theory for optimal crowdsourcing contests that mirrors the theory of optimal auction design: the optimal crowdsourcing contest is a virtual valuation optimizer (the virtual valuation function depends on the distribution of contestant skills and the number of contestants). We also compare crowdsourcing contests with more conventional means of procurement. In this comparison, crowdsourcing contests are relatively disadvantaged because the effort of losing contestants is wasted. Nonetheless, we show that crowdsourcing contests are 2-approximations to conventional methods for a large family of "regular" distributions, and 4-approximations, otherwise.

@misc{Chawla2011, abstract = { We study the design and approximation of optimal crowdsourcing contests. Crowdsourcing contests can be modeled as all-pay auctions because entrants must exert effort up-front to enter. Unlike all-pay auctions where a usual design objective would be to maximize revenue, in crowdsourcing contests, the principal only benefits from the submission with the highest quality. We give a theory for optimal crowdsourcing contests that mirrors the theory of optimal auction design: the optimal crowdsourcing contest is a virtual valuation optimizer (the virtual valuation function depends on the distribution of contestant skills and the number of contestants). We also compare crowdsourcing contests with more conventional means of procurement. In this comparison, crowdsourcing contests are relatively disadvantaged because the effort of losing contestants is wasted. Nonetheless, we show that crowdsourcing contests are 2-approximations to conventional methods for a large family of "regular" distributions, and 4-approximations, otherwise. }, added-at = {2011-11-19T21:17:03.000+0100}, author = {Chawla, Shuchi and Hartline, Jason D. and Sivan, Balasubramanian}, biburl = {https://www.bibsonomy.org/bibtex/2d12ea6e62b24f2a7a7e589ecbbe200ae/ea}, description = {[1111.2893] Optimal Crowdsourcing Contests}, interhash = {3aa85e3de4a71766a9e3665c6c71a91a}, intrahash = {d12ea6e62b24f2a7a7e589ecbbe200ae}, keywords = {citizenscience crowdsourcing}, note = {cite arxiv:1111.2893 Comment: The paper has 17 pages and 1 figure. It is to appear in the proceedings of ACM-SIAM Symposium on Discrete Algorithms 2012}, timestamp = {2011-11-19T21:17:03.000+0100}, title = {Optimal Crowdsourcing Contests}, url = {http://arxiv.org/abs/1111.2893}, year = 2011 }