795
views
0
recommends
+1 Recommend
0 collections
    4
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Amazon's Mechanical Turk : A New Source of Inexpensive, Yet High-Quality, Data?

      1 , 1 , 1
      Perspectives on Psychological Science
      SAGE Publications

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Amazon's Mechanical Turk (MTurk) is a relatively new website that contains the major elements required to conduct research: an integrated participant compensation system; a large participant pool; and a streamlined process of study design, participant recruitment, and data collection. In this article, we describe and evaluate the potential contributions of MTurk to psychology and other social sciences. Findings indicate that (a) MTurk participants are slightly more demographically diverse than are standard Internet samples and are significantly more diverse than typical American college samples; (b) participation is affected by compensation rate and task length, but participants can still be recruited rapidly and inexpensively; (c) realistic compensation rates do not affect data quality; and (d) the data obtained are at least as reliable as those obtained via traditional methods. Overall, MTurk can be used to obtain high-quality data inexpensively and rapidly.

          Related collections

          Author and article information

          Journal
          Perspectives on Psychological Science
          Perspect Psychol Sci
          SAGE Publications
          1745-6916
          1745-6924
          February 03 2011
          January 2011
          February 03 2011
          January 2011
          : 6
          : 1
          : 3-5
          Affiliations
          [1 ]Department of Psychology, University of Texas at Austin
          Article
          10.1177/1745691610393980
          26162106
          d87ceb6e-1ea2-4d0c-b891-116c9343a7a3
          © 2011

          http://journals.sagepub.com/page/policies/text-and-data-mining-license

          History

          Comments

          Comment on this article