TY - GEN
T1 - Optimal crowdsourcing contests
AU - Chawla, Shuchi
AU - Hartline, Jason D
AU - Sivan, Balasubramanian
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84860151940&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84860151940&partnerID=8YFLogxK
U2 - 10.1137/1.9781611973099.69
DO - 10.1137/1.9781611973099.69
M3 - Conference contribution
AN - SCOPUS:84860151940
SN - 9781611972108
T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
SP - 856
EP - 868
BT - Proceedings of the 23rd Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2012
PB - Association for Computing Machinery
T2 - 23rd Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2012
Y2 - 17 January 2012 through 19 January 2012
ER -