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