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2018 | OriginalPaper | Buchkapitel

Mechanical Novel: Crowdsourcing Complex Work Through Reflection and Revision

verfasst von : Joy Kim, Sarah Sterman, Allegra Argent Beal Cohen, Michael S. Bernstein

Erschienen in: Design Thinking Research

Verlag: Springer International Publishing

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Abstract

Crowdsourcing systems accomplish large tasks with scale and speed by breaking work down into independent parts. However, many types of complex creative work, such as fiction writing, have remained out of reach for crowds because work is tightly interdependent: changing one part of a story may trigger changes to the overall plot and vice versa. Taking inspiration from how expert authors write, we propose a technique for achieving interdependent complex goals with crowds. With this technique, the crowd loops between reflection, to select a high-level goal, and revision, to decompose that goal into low-level, actionable tasks. We embody this approach in Mechanical Novel, a system that crowdsources short fiction stories on Amazon Mechanical Turk. In a field experiment, Mechanical Novel resulted in higher-quality stories than an iterative crowdsourcing workflow. Our findings suggest that orienting crowd work around high-level goals may enable workers to coordinate their effort to accomplish complex work.

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Fußnoten
1
This story length struck a balance between being long enough to make it difficult to coordinate work and short enough to complete in a reasonable amount of time on Mechanical Turk.
 
2
The federal minimum wage at the time of this writing was $7.25.
 
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Metadaten
Titel
Mechanical Novel: Crowdsourcing Complex Work Through Reflection and Revision
verfasst von
Joy Kim
Sarah Sterman
Allegra Argent Beal Cohen
Michael S. Bernstein
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-60967-6_5