Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
![Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/generic/no-book-image.png)
Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool
by
Robinson, Jonathan
, Rosenzweig, Cheskie
, Litman, Leib
, Moss, Aaron J
in
Adult
/ Behavioral Research - methods
/ Behavioral Research - standards
/ Bias
/ Biology and Life Sciences
/ Crowdsourcing - methods
/ Crowdsourcing - standards
/ Data Accuracy
/ Data collection
/ Data Collection - methods
/ Data Collection - standards
/ Datasets as Topic - standards
/ Female
/ Humans
/ Information management
/ Internet
/ Male
/ Medicine and Health Sciences
/ Methods
/ Middle Aged
/ Patient Selection
/ Physical Sciences
/ Practice Guidelines as Topic
/ Psychology
/ Quality
/ Research and Analysis Methods
/ Researchers
/ Retirement benefits
/ Sample Size
/ Sampling
/ Sampling Studies
/ Selection Bias
/ Social Sciences
/ Studies
/ Work
/ Workers
/ Young Adult
2019
![Hey, we have placed the reservation for you!](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/illustrations/modal-success.png)
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
![Oops! Something went wrong.](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/illustrations/modal-fail.png)
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
![](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/generic/no-book-image.png)
Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool
by
Robinson, Jonathan
, Rosenzweig, Cheskie
, Litman, Leib
, Moss, Aaron J
in
Adult
/ Behavioral Research - methods
/ Behavioral Research - standards
/ Bias
/ Biology and Life Sciences
/ Crowdsourcing - methods
/ Crowdsourcing - standards
/ Data Accuracy
/ Data collection
/ Data Collection - methods
/ Data Collection - standards
/ Datasets as Topic - standards
/ Female
/ Humans
/ Information management
/ Internet
/ Male
/ Medicine and Health Sciences
/ Methods
/ Middle Aged
/ Patient Selection
/ Physical Sciences
/ Practice Guidelines as Topic
/ Psychology
/ Quality
/ Research and Analysis Methods
/ Researchers
/ Retirement benefits
/ Sample Size
/ Sampling
/ Sampling Studies
/ Selection Bias
/ Social Sciences
/ Studies
/ Work
/ Workers
/ Young Adult
2019
![Oops! Something went wrong.](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/illustrations/modal-fail.png)
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
![Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/generic/no-book-image.png)
Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool
by
Robinson, Jonathan
, Rosenzweig, Cheskie
, Litman, Leib
, Moss, Aaron J
in
Adult
/ Behavioral Research - methods
/ Behavioral Research - standards
/ Bias
/ Biology and Life Sciences
/ Crowdsourcing - methods
/ Crowdsourcing - standards
/ Data Accuracy
/ Data collection
/ Data Collection - methods
/ Data Collection - standards
/ Datasets as Topic - standards
/ Female
/ Humans
/ Information management
/ Internet
/ Male
/ Medicine and Health Sciences
/ Methods
/ Middle Aged
/ Patient Selection
/ Physical Sciences
/ Practice Guidelines as Topic
/ Psychology
/ Quality
/ Research and Analysis Methods
/ Researchers
/ Retirement benefits
/ Sample Size
/ Sampling
/ Sampling Studies
/ Selection Bias
/ Social Sciences
/ Studies
/ Work
/ Workers
/ Young Adult
2019
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
![We have requested the book for you!](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/illustrations/modal-success.png)
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
![Oops! Something went wrong.](https://www.mbrl.ae/o/mbrl-theme/images/site-assets/illustrations/modal-fail.png)
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool
![Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool](https://syndetics.com/index.aspx?isbn=/mc.gif&issn=1932-6203&client=MBRL&type=mbrl)
Journal Article
Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool
2019
Request now
and choose the collection method
Overview
Mechanical Turk (MTurk) is a common source of research participants within the academic community. Despite MTurk's utility and benefits over traditional subject pools some researchers have questioned whether it is sustainable. Specifically, some have asked whether MTurk workers are too familiar with manipulations and measures common in the social sciences, the result of many researchers relying on the same small participant pool. Here, we show that concerns about non-naivete on MTurk are due less to the MTurk platform itself and more to the way researchers use the platform. Specifically, we find that there are at least 250,000 MTurk workers worldwide and that a large majority of US workers are new to the platform each year and therefore relatively inexperienced as research participants. We describe how inexperienced workers are excluded from studies, in part, because of the worker reputation qualifications researchers commonly use. Then, we propose and evaluate an alternative approach to sampling on MTurk that allows researchers to access inexperienced participants without sacrificing data quality. We recommend that in some cases researchers should limit the number of highly experienced workers allowed in their study by excluding these workers or by stratifying sample recruitment based on worker experience levels. We discuss the trade-offs of different sampling practices on MTurk and describe how the above sampling strategies can help researchers harness the vast and largely untapped potential of the Mechanical Turk participant pool.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
This website uses cookies to ensure you get the best experience on our website.