Running Experiments on Amazon Mechanical Turk
Judgment and Decision Making, Vol. 5, No. 5, 411-419
9 Pages Posted: 1 Jul 2010 Last revised: 25 Jan 2015
Date Written: June 24, 2010
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.
Keywords: Experimentation, Judgment and decision-making, Online research
JEL Classification: C9, J2
Suggested Citation: Suggested Citation