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Intertemporal Differences Among MTurk Workers

Time-Based Sample Variations and Implications for Online Data Collection

Bibliographic Data

ID16911908
AuthorsLinda Casey (0000-0002-8232-7925, Harvard University), Logan S Casey, Joan Chandler (0000-0001-8151-0915, University of Michigan, corresponding author), Jesse Chandler, Adam Seth Levine (0000-0003-4014-1003, Cornell University), A Proctor (0000-0002-2469-644X, Princeton University), Dara Z Strolovitch (0000-0002-1051-8036, Princeton University)
Year2017
Volume7
Issue2
Publication date2017-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/2158244017712774
OpenAlexW2625865465
LanguageEN
Citations received27
References cited48

The online labor market Amazon Mechanical Turk (MTurk) is an increasingly popular source of respondents for social science research. A growing body of research has examined the demographic composition of MTurk workers as compared with that of other populations. While these comparisons have revealed the ways in which MTurk workers are and are not representative of the general population, variations among samples drawn from MTurk have received less attention. This article focuses on whether MTurk sample composition varies as a function of time. Specifically, we examine whether demographic characteristics vary by (a) time of day, (b) day of week, and serial position (i.e., earlier or later in data collection), both (c) across the entire data collection and (d) within specific batches. We find that day of week differences are minimal, but that time of day and serial position are associated with small but important variations in demographic composition. This demonstrates that MTurk samples cannot be presumed identical across different studies, potentially affecting reliability, validity, and efforts to reproduce findings

Amazon rainforest · Biology · Data collection · Population · Sociology · Statistics · Demography · Digital Marketing and Social Media · Mathematics · Psychology · Sharing Economy and Platforms · Technology Adoption and User Behaviour

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Unique citing works27
Citations per year3,86
Citation span2019 - 2026 (8)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 23
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