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Amazon Mechanical Turk: A Web-Based Tool for Facilitating Experimental Research in ANLP

Amazon Mechanical Turk: A Web-Based Tool for Facilitating Experimental Research in ANLP
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Author(s): Amber Chauncey Strain (The University of Memphis, Institute for Intelligent Systems, USA)and Lucille M. Booker (The University of Memphis, Institute for Intelligent Systems, USA)
Copyright: 2012
Pages: 13
Source title: Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches
Source Author(s)/Editor(s): Chutima Boonthum-Denecke (Hampton University, USA), Philip M. McCarthy (The University of Memphis, USA)and Travis Lamkin (University of Memphis, USA)
DOI: 10.4018/978-1-61350-447-5.ch007

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Abstract

One of the major challenges of ANLP research is the constant balancing act between the need for large samples, and the excessive time and monetary resources necessary for acquiring those samples. Amazon’s Mechanical Turk (MTurk) is a web-based data collection tool that has become a premier resource for researchers who are interested in optimizing their sample sizes and minimizing costs. Due to its supportive infrastructure, diverse participant pool, quality of data, and time and cost efficiency, MTurk seems particularly suitable for ANLP researchers who are interested in gathering large, high quality corpora in relatively short time frames. In this chapter, the authors first provide a broad description of the MTurk interface. Next, they describe the steps for acquiring IRB approval of MTurk experiments, designing experiments using the MTurk dashboard, and managing data. Finally, the chapter concludes by discussing the potential benefits and limitations of using MTurk for ANLP experimentation.

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