  Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and
etc.) emerged in recent years that allow requesters from all around the world
to post tasks and seek help from an equally global pool of workers. However,
intrinsic incentive problems reside in crowdsourcing applications as workers
and requester are selfish and aim to strategically maximize their own benefit.
In this paper, we propose to provide incentives for workers to exert effort
using a novel game-theoretic model based on repeated games. As there is always
a gap in the social welfare between the non-cooperative equilibria emerging
when workers pursue their self-interests and the desirable Pareto efficient
outcome, we propose a novel class of incentive protocols based on social norms
which integrates reputation mechanisms into the existing pricing schemes
currently implemented on crowdsourcing websites, in order to improve the
performance of the non-cooperative equilibria emerging in such applications. We
first formulate the exchanges on a crowdsourcing website as a two-sided market
where requesters and workers are matched and play gift-giving games repeatedly.
Subsequently, we study the protocol designer's problem of finding an optimal
and sustainable (equilibrium) protocol which achieves the highest social
welfare for that website. We prove that the proposed incentives protocol can
make the website operate close to Pareto efficiency. Moreover, we also examine
an alternative scenario, where the protocol designer aims at maximizing the
revenue of the website and evaluate the performance of the optimal protocol.
