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MTurk ‘Unscrubbed’: Exploring the good, the ‘Super’, and the unreliable on Amazon’s Mechanical Turk


  • Jeanette A.M.J. Deetlefs

    (School of Marketing, UNSW Business School, UNSW)

  • Mathew Chylinski

    (School of Marketing, UNSW Business School, UNSW)

  • Andreas Ortmann

    (School of Economics, UNSW Business School, UNSW)


Widely accepted as a low-cost, fast-turnaround solution with acceptable validity, Amazon’s Mechanical Turk (MTurk) is increasingly being used to source participants for academic studies (Berinsky et al. 2012; Bohannon 2011; Chandler et al. 2014; Mason and Suri 2012). Yet two commonly raised concerns remain: the presence of quasi-professional respondents, or “Super-Turkers”, and the presence of “Spammers”, those that compromise quality while optimising their pay rate. We isolate the influence on research results of experienced subjects (Super-Turkers), and of unreliable subjects (Spammers), jointly and separately. Jointly including these subjects produces very similar results to jointly excluding them, yet effect sizes decrease disproportionately to their sample representation. Furthermore, separately including experienced subjects in research results is shown to be as problematic as inclusion of unreliable subjects, although the noise introduced by these subjects is divergent and measure dependent. Hence removing only one of these types of respondents can be even more damaging to the reliability of results, than including both.

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  • Jeanette A.M.J. Deetlefs & Mathew Chylinski & Andreas Ortmann, 2015. "MTurk ‘Unscrubbed’: Exploring the good, the ‘Super’, and the unreliable on Amazon’s Mechanical Turk," Discussion Papers 2015-20, School of Economics, The University of New South Wales.
  • Handle: RePEc:swe:wpaper:2015-20a

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    1. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    2. Camerer, Colin F & Hogarth, Robin M, 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 7-42, December.
    3. van Rooij, Maarten & Lusardi, Annamaria & Alessie, Rob, 2011. "Financial literacy and stock market participation," Journal of Financial Economics, Elsevier, vol. 101(2), pages 449-472, August.
    4. Todd L. Cherry & Peter Frykblom & Jason F. Shogren, 2002. "Hardnose the Dictator," American Economic Review, American Economic Association, vol. 92(4), pages 1218-1221, September.
    5. Lusardi, Annamaria & Mitchell, Olivia S., 2007. "Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth," Journal of Monetary Economics, Elsevier, vol. 54(1), pages 205-224, January.
    6. Hazel Bateman & Christine Eckert & John Geweke & Jordan Louviere & Susan Thorp & Stephen Satchell, 2012. "Financial Competence and Expectations Formation: Evidence from Australia," The Economic Record, The Economic Society of Australia, vol. 88(280), pages 39-63, March.
    7. Annamaria Lusardi & Olivia S. Mitchell, 2017. "How Ordinary Consumers Make Complex Economic Decisions: Financial Literacy and Retirement Readiness," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 1-31, September.
    8. Uri Gneezy & Jan Potters, 1997. "An Experiment on Risk Taking and Evaluation Periods," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 631-645.
    9. Catherine C. Eckel & Philip J. Grossman, 2008. "Forecasting Risk Attitudes: An Experimental Study Using Actual and Forecast Gamble Choices," Monash Economics Working Papers archive-01, Monash University, Department of Economics.
    10. Charness, Gary & Gneezy, Uri & Imas, Alex, 2013. "Experimental methods: Eliciting risk preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 43-51.
    11. Charness, Gary & Karni, Edi & Levin, Dan, 2010. "On the conjunction fallacy in probability judgment: New experimental evidence regarding Linda," Games and Economic Behavior, Elsevier, vol. 68(2), pages 551-556, March.
    12. Kaufman, Carol Felker & Lane, Paul M & Lindquist, Jay D, 1991. "Exploring More Than 24 Hours a Day: A Preliminary Investigation of Polychronic Time Use," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(3), pages 392-401, December.
    13. Reilly, Michael D, 1982. "Working Wives and Convenience Consumption," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 8(4), pages 407-418, March.
    14. David G. Rand & Alexander Peysakhovich & Gordon T. Kraft-Todd & George E. Newman & Owen Wurzbacher & Martin A. Nowak & Joshua D. Greene, 2014. "Social heuristics shape intuitive cooperation," Nature Communications, Nature, vol. 5(1), pages 1-12, May.
    15. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research:'s Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
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    Cited by:

    1. Antonio A. Arechar & Gordon T. Kraft-Todd & David G. Rand, 2017. "Turking overtime: how participant characteristics and behavior vary over time and day on Amazon Mechanical Turk," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 3(1), pages 1-11, July.

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    More about this item


    data collection; experimentation; field experiment; internet; Mechanical Turk;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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