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Turking overtime: how participant characteristics and behavior vary over time and day on Amazon Mechanical Turk

Published online by Cambridge University Press:  17 January 2025

Antonio A. Arechar Open the ORCID record for Antonio A. Arechar [Opens in a new window] ,
Gordon T. Kraft-Todd  and
David G. Rand
Antonio A. Arechar*
Affiliation:
Department of Psychology, Yale University, 2 Hillhouse Ave., New Haven, CT 06511, USA
Gordon T. Kraft-Todd
Affiliation:
Department of Psychology, Yale University, 2 Hillhouse Ave., New Haven, CT 06511, USA
David G. Rand*
Affiliation:
Department of Psychology, Yale University, 2 Hillhouse Ave., New Haven, CT 06511, USA Department of Economics, Yale University, 28 Hillhouse Ave., New Haven, CT 06511, USA School of Management, Yale University, 165 Whitney Ave., New Haven, CT 06511, USA
*
e-mail: antonio.alonso@yale.edu
e-mail: david.rand@yale.edu
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Abstract

Online experiments allow researchers to collect datasets at times not typical of laboratory studies. We recruit 2336 participants from Amazon Mechanical Turk to examine if participant characteristics and behaviors differ depending on whether the experiment is conducted during the day versus night, and on weekdays versus weekends. Participants make incentivized decisions involving prosociality, punishment, and discounting, and complete a demographic and personality survey. We find no time or day differences in behavior, but do find that participants at nights and on weekends are less experienced with online studies; on weekends are less reflective; and at night are less conscientious and more neurotic. These results are largely robust to finer-grained measures of time and day. We also find that those who participated earlier in the course of the study are more experienced, reflective, and agreeable, but less charitable than later participants.

Keywords

CooperationHonestyDecision-makingTime of dayMTurkSelf-control

JEL classification

C80: General C90: General

Information

Type
Original Paper
Information
Journal of the Economic Science Association , Volume 3 , Issue 1 , July 2017 , pp. 1 - 11
Copyright
Copyright © Economic Science Association 2017

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Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s40881-017-0035-0) contains supplementary material, which is available to authorized users.

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