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Identifying and Rewarding Subcrowds in Crowdsourcing

. Identifying and rewarding truthful workers are key to the sustainability of crowdsourcing platforms. In this paper, we present a clustering based rewarding mechanism that rewards workers based on their truthfulness while accommodating the differences in work-ers’ preferences. Experimental results show that the proposed approach can effectively discover subcrowds under various conditions, and truthful workers are better rewarded than less truthful ones. Experimental results show that the proposed clustering approach is able to identify subcrowds even with a signiﬁcant amount of the population being untruthful. Results also show that the workers will receive more rewards if they provide more truthful answers.