Inserting Micro-Breaks into Crowdsourcing Workflows

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Abstract

Participants in human computation workflows may become fatigued or get bored over long, interminable working hours. This leads to a slump of motivation and morale, which in the long run causes reductions in both productivity and work quality. In this paper we propose an initial investigation into possible ways to alleviate worker fatigue and boredom by employing micro-breaks that provide timely relax to workers during long sequences of tasks. We experimentally test micro-breaks on Amazon’s Mechanical Turk, showing that micro-breaks can significantly improve worker retention rate as task batches reach hours in length, and appear to increase overall worker engagement and commitment to their work.

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APA

Rzeszotarski, J. M., Chi, E., Paritosh, P., & Dai, P. (2013). Inserting Micro-Breaks into Crowdsourcing Workflows. In Proceedings of the 1st AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2013 (pp. 62–63). AAAI Press. https://doi.org/10.1609/hcomp.v1i1.13127

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