Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers

Abstract Crowdsourcing services—particularly Amazon Mechanical Turk—have made it easy for behavioral scientists to recruit research participants. However, researchers have overlooked crucial differences between crowdsourcing and traditional recruitment methods that provide unique opportunities and c...
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Autor*in:	Chandler, Jesse [verfasserIn] Mueller, Pam Paolacci, Gabriele

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	Crowdsourcing Internet research Data quality Longitudinal research Mechanical Turk MTurk

Anmerkung:	© Psychonomic Society, Inc. 2013

Übergeordnetes Werk:	Enthalten in: Behavior research methods, instruments & computers - Austin, Tex. : Psychonomic Society Publ., 1984, 46(2013), 1 vom: 09. Juli, Seite 112-130
Übergeordnetes Werk:	volume:46 ; year:2013 ; number:1 ; day:09 ; month:07 ; pages:112-130

Links:	Volltext

DOI / URN:	10.3758/s13428-013-0365-7

Katalog-ID:	SPR031701647

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allfieldsSound	10.3758/s13428-013-0365-7 doi (DE-627)SPR031701647 (SPR)s13428-013-0365-7-e DE-627 ger DE-627 rakwb eng Chandler, Jesse verfasserin aut Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Psychonomic Society, Inc. 2013 Abstract Crowdsourcing services—particularly Amazon Mechanical Turk—have made it easy for behavioral scientists to recruit research participants. However, researchers have overlooked crucial differences between crowdsourcing and traditional recruitment methods that provide unique opportunities and challenges. We show that crowdsourced workers are likely to participate across multiple related experiments and that researchers are overzealous in the exclusion of research participants. We describe how both of these problems can be avoided using advanced interface features that also allow prescreening and longitudinal data collection. Using these techniques can minimize the effects of previously ignored drawbacks and expand the scope of crowdsourcing as a tool for psychological research. Crowdsourcing (dpeaa)DE-He213 Internet research (dpeaa)DE-He213 Data quality (dpeaa)DE-He213 Longitudinal research (dpeaa)DE-He213 Mechanical Turk (dpeaa)DE-He213 MTurk (dpeaa)DE-He213 Mueller, Pam aut Paolacci, Gabriele aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 46(2013), 1 vom: 09. Juli, Seite 112-130 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:46 year:2013 number:1 day:09 month:07 pages:112-130 https://dx.doi.org/10.3758/s13428-013-0365-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 46 2013 1 09 07 112-130
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author	Chandler, Jesse
spellingShingle	Chandler, Jesse misc Crowdsourcing misc Internet research misc Data quality misc Longitudinal research misc Mechanical Turk misc MTurk Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers
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topic_title	Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers Crowdsourcing (dpeaa)DE-He213 Internet research (dpeaa)DE-He213 Data quality (dpeaa)DE-He213 Longitudinal research (dpeaa)DE-He213 Mechanical Turk (dpeaa)DE-He213 MTurk (dpeaa)DE-He213
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title	Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers
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title_full	Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers
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title_sort	nonnaïveté among amazon mechanical turk workers: consequences and solutions for behavioral researchers
title_auth	Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers
abstract	Abstract Crowdsourcing services—particularly Amazon Mechanical Turk—have made it easy for behavioral scientists to recruit research participants. However, researchers have overlooked crucial differences between crowdsourcing and traditional recruitment methods that provide unique opportunities and challenges. We show that crowdsourced workers are likely to participate across multiple related experiments and that researchers are overzealous in the exclusion of research participants. We describe how both of these problems can be avoided using advanced interface features that also allow prescreening and longitudinal data collection. Using these techniques can minimize the effects of previously ignored drawbacks and expand the scope of crowdsourcing as a tool for psychological research. © Psychonomic Society, Inc. 2013
abstractGer	Abstract Crowdsourcing services—particularly Amazon Mechanical Turk—have made it easy for behavioral scientists to recruit research participants. However, researchers have overlooked crucial differences between crowdsourcing and traditional recruitment methods that provide unique opportunities and challenges. We show that crowdsourced workers are likely to participate across multiple related experiments and that researchers are overzealous in the exclusion of research participants. We describe how both of these problems can be avoided using advanced interface features that also allow prescreening and longitudinal data collection. Using these techniques can minimize the effects of previously ignored drawbacks and expand the scope of crowdsourcing as a tool for psychological research. © Psychonomic Society, Inc. 2013
abstract_unstemmed	Abstract Crowdsourcing services—particularly Amazon Mechanical Turk—have made it easy for behavioral scientists to recruit research participants. However, researchers have overlooked crucial differences between crowdsourcing and traditional recruitment methods that provide unique opportunities and challenges. We show that crowdsourced workers are likely to participate across multiple related experiments and that researchers are overzealous in the exclusion of research participants. We describe how both of these problems can be avoided using advanced interface features that also allow prescreening and longitudinal data collection. Using these techniques can minimize the effects of previously ignored drawbacks and expand the scope of crowdsourcing as a tool for psychological research. © Psychonomic Society, Inc. 2013
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title_short	Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers
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