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Crowdsourcing for cognitive science - the utility of smartphones

Brown, HR; Zeidman, P; Smittenaar, P; Adams, RA; McNab, F; Rutledge, RB; Dolan, RJ; (2014) Crowdsourcing for cognitive science - the utility of smartphones. PLoS One , 9 (7) , Article e100662. 10.1371/journal.pone.0100662. Green open access

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Abstract

By 2015, there will be an estimated two billion smartphone users worldwide. This technology presents exciting opportunities for cognitive science as a medium for rapid, large-scale experimentation and data collection. At present, cost and logistics limit most study populations to small samples, restricting the experimental questions that can be addressed. In this study we investigated whether the mass collection of experimental data using smartphone technology is valid, given the variability of data collection outside of a laboratory setting. We presented four classic experimental paradigms as short games, available as a free app and over the first month 20,800 users submitted data. We found that the large sample size vastly outweighed the noise inherent in collecting data outside a controlled laboratory setting, and show that for all four games canonical results were reproduced. For the first time, we provide experimental validation for the use of smartphones for data collection in cognitive science, which can lead to the collection of richer data sets and a significant cost reduction as well as provide an opportunity for efficient phenotypic screening of large populations.

Type: Article
Title: Crowdsourcing for cognitive science - the utility of smartphones
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pone.0100662
Publisher version: http://dx.doi.org/10.1371/journal.pone.0100662
Language: English
Additional information: © 2014 Brown et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1435377
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