eprintid: 1435377
rev_number: 42
eprint_status: archive
userid: 608
dir: disk0/01/43/53/77
datestamp: 2014-07-19 19:45:10
lastmod: 2021-09-19 22:31:16
status_changed: 2015-09-14 08:20:32
type: article
metadata_visibility: show
item_issues_count: 0
creators_name: Brown, HR
creators_name: Zeidman, P
creators_name: Smittenaar, P
creators_name: Adams, RA
creators_name: McNab, F
creators_name: Rutledge, RB
creators_name: Dolan, RJ
title: Crowdsourcing for cognitive science - the utility of smartphones
ispublished: pub
divisions: UCL
divisions: B02
divisions: C07
divisions: D07
divisions: F83
divisions: B04
divisions: C05
divisions: F48
note: © 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.
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.
date: 2014-07-15
official_url: http://dx.doi.org/10.1371/journal.pone.0100662
vfaculties: VFBRS
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
article_type_text: Journal Article
verified: verified_manual
elements_source: PubMed
elements_id: 965094
doi: 10.1371/journal.pone.0100662
pii: PONE-D-13-27475
lyricists_name: Adams, Richard
lyricists_name: Dolan, Raymond
lyricists_name: Rutledge, Robb
lyricists_name: Smittenaar, Peter
lyricists_name: Zeidman, Peter
lyricists_id: RAADA06
lyricists_id: RJDOL46
lyricists_id: RRUTL30
lyricists_id: PBSMI27
lyricists_id: PZEID23
full_text_status: public
publication: PLoS One
volume: 9
number: 7
article_number: e100662
event_location: United States
citation:        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 <https://doi.org/10.1371/journal.pone.0100662>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1435377/1/journal.pone.0100662.pdf