Running Experiments on Amazon Mechanical Turk
Erasmus University - Rotterdam School of Management
Princeton University - Woodrow Wilson School of Public and International Affairs
Panagiotis G. Ipeirotis
New York University - Leonard N. Stern School of Business
June 24, 2010
Judgment and Decision Making, Vol. 5, No. 5, 411-419
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 participants 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 participants, 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.
Number of Pages in PDF File: 9
Keywords: Experimentation, Judgment and decision-making, Online research
JEL Classification: C9, J2Accepted Paper Series
Date posted: July 1, 2010 ; Last revised: September 2, 2010
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