DocumentCode
652699
Title
Affect and Creative Performance on Crowdsourcing Platforms
Author
Morris, Robert R. ; Dontcheva, Mira ; Finkelstein, Adam ; Gerber, Elizabeth
Author_Institution
MIT Media Lab., Massachusetts Inst. of Technol., Cambridge, MA, USA
fYear
2013
fDate
2-5 Sept. 2013
Firstpage
67
Lastpage
72
Abstract
Performance on crowd sourcing platforms varies greatly, especially for tasks requiring significant cognitive effort or creative insight. Researchers have proposed several techniques to address these problems, yet few have considered the role of affect, despite the well-established link between positive affect and creative performance. In this paper, we examine two affective techniques to boost creativity on crowd sourcing platforms - affective priming and affective pre-screening. Across three experiments, we find divergent results, depending on which technique is used. We find that not all happy crowd workers are alike. Those that are primed to feel happy exhibit enhanced creative performance, whereas those that merely report feeling happy exhibit impaired creative performance. We examine these findings in light of preexisting research on creativity, affect, and mood saliency. Lastly, we show how our findings have implications not only for crowd sourcing platforms, but also for other human-computer interaction scenarios that involve affect and creative performance.
Keywords
groupware; outsourcing; affect performance; creative performance; crowdsourcing platforms; mood saliency; Affective computing; Atmospheric measurements; Educational institutions; Mood; Music; Particle measurements; Problem-solving; affective computing; affective priming; affective self-report; creativity; crowdsourcing;
fLanguage
English
Publisher
ieee
Conference_Titel
Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on
Conference_Location
Geneva
ISSN
2156-8103
Type
conf
DOI
10.1109/ACII.2013.18
Filename
6681409
Link To Document