Journal ArticleDOI
Validity and Mechanical Turk
Kyle A. Thomas,Scott Clifford +1 more
TLDR
It is found that insufficient attention is no more a problem among MTurk samples than among other commonly used convenience or high-quality commercial samples, and that MTurK participants buy into interactive experiments and trust researchers as much as participants in laboratory studies.About:
This article is published in Computers in Human Behavior.The article was published on 2017-12-01. It has received 387 citations till now.read more
Citations
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Journal ArticleDOI
MTurk Research: Review and Recommendations:
TL;DR: The use of Amazon's Mechanical Turk (MTurk) in management research has increased over 2,117% in recent years, from 6 papers in 2012 to 133 in 2019.
Journal ArticleDOI
Online panels in social science research: Expanding sampling methods beyond Mechanical Turk
TL;DR: It is concluded that online research panels offer a unique opportunity for research, yet one with some important trade-offs, as compared with traditional student subject pools.
Journal ArticleDOI
The Shape of and Solutions to the MTurk Quality Crisis
TL;DR: This work provides both a post-hoc method for identifying fraudulent respondents using an original R package and an associated online application and an a priori method using JavaScript and PHP code in Qualtrics to block fraudulent respondents from participating.
Journal ArticleDOI
Are Manipulation Checks Necessary
TL;DR: The use of manipulation checks in mediational analyses does not rule out confounding variables, as any unmeasured variables that correlate with the manipulation check may still drive the relationship.
Journal ArticleDOI
The shape of and solutions to the MTurk quality crisis
Ryan Kennedy,Scott Clifford,Tyler J. Burleigh,Philip D. Waggoner,Ryan Jewell,Nicholas Winter +5 more
TL;DR: In this article, an easy-to-use application for identifying fraud in the existing datasets and a method for blocking fraudulent respondents in Qualtrics surveys is proposed. But, the authors do not consider the impact of these fraudulent respondents on the quality of the data.
References
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Journal ArticleDOI
Amazon's Mechanical Turk A New Source of Inexpensive, Yet High-Quality, Data?
TL;DR: Findings indicate that MTurk can be used to obtain high-quality data inexpensively and rapidly and the data obtained are at least as reliable as those obtained via traditional methods.
Running experiments on Amazon Mechanical Turk
TL;DR: The authors presented new demographic data about the Mechanical Turk subject population, reviewed the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and compared the magnitude of effects obtained using Mechanical Turk and traditional subject pools.
Journal ArticleDOI
Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk
TL;DR: It is shown that respondents recruited in this manner are often more representative of the U.S. population than in-person convenience samples but less representative than subjects in Internet-based panels or national probability samples.
Posted Content
Running experiments on Amazon Mechanical Turk
TL;DR: The authors presented new demographic data about the Mechanical Turk subject population, reviewed the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and compared the magnitude of effects obtained using Mechanical Turk and traditional subject pools.
Posted Content
Conducting Behavioral Research on Amazon's Mechanical Turk
TL;DR: In this article, the authors demonstrate how to use Mechanical Turk for conducting behavioral research and lower the barrier to entry for researchers who could benefit from this platform, and illustrate the mechanics of putting a task on Mechanical Turk including recruiting subjects, executing the task, and reviewing the work submitted.