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ACM Transactions on Computer-Human Interaction (TOCHI) - Special issue on human-computer interaction in the new millennium, Part 1
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This paper studied how social transparency and different peer-dependent reward schemes (i.e., individual, teamwork, and competition) affect the outcomes of crowdsourcing. The results showed that when social transparency was increased by asking otherwise anonymous workers to share their demographic information (e.g., name, nationality) to the paired worker, they performed significantly better. A more detailed analysis showed that in a teamwork reward scheme, in which the reward of the paired workers depended only on the collective outcomes, increasing social transparency could offset effects of social loafing by making them more accountable to their teammates. In a competition reward scheme, in which workers competed against each other and the reward depended on how much they outperformed their opponent, increasing social transparency could augment effects of social facilitation by providing more incentives for them to outperform their opponent. The results suggested that a careful combination of methods that increase social transparency and different reward schemes can significantly improve crowdsourcing outcomes.