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

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • 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:2015-20
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    References listed on IDEAS

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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

    Keywords

    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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