Running Experiments on Amazon Mechanical Turk

Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechan...

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Vydané v:	Judgment and Decision Making Ročník 5; číslo 5; s. 411 - 419
Hlavní autori:	Paolacci, Gabriele, Chandler, Jesse, Ipeirotis, Panagiotis G.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Tallahassee Society for Judgment and Decision Making 01.08.2010 Cambridge University Press
Edícia:	Judgment and Decision Making
Predmet:	Decision making Demographics experimentation Experiments Income distribution Internet Labor market online research Population Wages & salaries Workers online research experimentation
ISSN:	1930-2975, 1930-2975
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool.
AbstractList	Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool.
Author	Jesse Chandler Gabriele Paolacci Panagiotis G. Ipeirotis
Author_xml	– sequence: 1 givenname: Gabriele surname: Paolacci fullname: Paolacci, Gabriele – sequence: 2 givenname: Jesse surname: Chandler fullname: Chandler, Jesse – sequence: 3 givenname: Panagiotis G. surname: Ipeirotis fullname: Ipeirotis, Panagiotis G.
BackLink	http://econpapers.repec.org/article/jdmjournl/v_3a5_3ay_3a2010_3ai_3a5_3ap_3a411-419.htm$$DView record in RePEc
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Title	Running Experiments on Amazon Mechanical Turk
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