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Conducting behavioral research on Amazon’s Mechanical Turk

Overview of attention for article published in Behavior Research Methods, June 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
1 news outlet
twitter
9 tweeters

Citations

dimensions_citation
1421 Dimensions

Readers on

mendeley
1664 Mendeley
citeulike
5 CiteULike
Title
Conducting behavioral research on Amazon’s Mechanical Turk
Published in
Behavior Research Methods, June 2011
DOI 10.3758/s13428-011-0124-6
Pubmed ID
Authors

Winter Mason, Siddharth Suri

Abstract

Amazon's Mechanical Turk is an online labor market where requesters post jobs and workers choose which jobs to do for pay. The central purpose of this article is to demonstrate how to use this Web site for conducting behavioral research and to lower the barrier to entry for researchers who could benefit from this platform. We describe general techniques that apply to a variety of types of research and experiments across disciplines. We begin by discussing some of the advantages of doing experiments on Mechanical Turk, such as easy access to a large, stable, and diverse subject pool, the low cost of doing experiments, and faster iteration between developing theory and executing experiments. While other methods of conducting behavioral research may be comparable to or even better than Mechanical Turk on one or more of the axes outlined above, we will show that when taken as a whole Mechanical Turk can be a useful tool for many researchers. We will discuss how the behavior of workers compares with that of experts and laboratory subjects. Then we will illustrate the mechanics of putting a task on Mechanical Turk, including recruiting subjects, executing the task, and reviewing the work that was submitted. We also provide solutions to common problems that a researcher might face when executing their research on this platform, including techniques for conducting synchronous experiments, methods for ensuring high-quality work, how to keep data private, and how to maintain code security.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,664 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 120 7%
United Kingdom 28 2%
Germany 15 <1%
Canada 12 <1%
Netherlands 7 <1%
Switzerland 7 <1%
Brazil 4 <1%
Spain 4 <1%
Australia 4 <1%
Other 39 2%
Unknown 1424 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 606 36%
Student > Master 228 14%
Researcher 201 12%
Student > Doctoral Student 144 9%
Student > Bachelor 123 7%
Other 362 22%
Readers by discipline Count As %
Psychology 520 31%
Computer Science 258 16%
Social Sciences 211 13%
Business, Management and Accounting 211 13%
Unspecified 148 9%
Other 316 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 April 2019.
All research outputs
#872,737
of 13,194,193 outputs
Outputs from Behavior Research Methods
#77
of 1,135 outputs
Outputs of similar age
#5,726
of 84,682 outputs
Outputs of similar age from Behavior Research Methods
#3
of 19 outputs
Altmetric has tracked 13,194,193 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,135 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 84,682 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.