Separate but equal? A comparison of participants and data gathered via Amazon's MTurk, social media, and face-to-face behavioral testing

By Krista Casler, Lydia Bickel, Elizabeth Hackett. 2013

1,705 citations recorded by the source corpus.

Subfields: Applied Psychology, Literature and Literary Theory, Sociology and Political Science

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Citations in the corpus

Manipulating and Measuring Model Interpretability (2018, background): “tudies show that data from high reputation Mechanical Turk workers are comparable to data from commercial panels and university pools when assessing factors such as attentiveness, honesty, and effort [11, 13, 16, 53, 59]. (a) Clear, two-feature condition (CLEAR-2). (b) Black-box, two-feature conditi”
How psychological and contextual factors contribute to travelers’ propensity to choose green hotels? (2019, background): “MTurk has become a very popular channel through which behavioral researchers collect data as it is cost effective, fast, and easily accessible to a wide range of participant demographics (Casler et al., 2013).”
Do Investors Value Sustainability? A Natural Experiment Examining Ranking and Fund Flows (2019, background): “18Research examining this platform nds that participants recruited through MTurk tend to perform similarly on tasks (Casler et al., 2013) and better in attention checks (Hauser and Schwarz, 2016) than traditional participant pools traditionally recruited through labs, while representing a more…”
An Evaluation of Amazon’s Mechanical Turk, Its Rapid Rise, and Its Effective Use (2018, background): “One feature of MTurk is the ability to collect large samples that are often more demo-graphically diverse than typical undergraduate populations (Buhrmester, Kwang, & Gosling, 2011; Casler, Bickel, & Hackett, 2013).”
In Related News, That Was Wrong: The Correction of Misinformation Through Related Stories Functionality in Social Media (2015, result): “Previous research has suggested that Mechanical Turk samples are similar to other Internet samples and substantially more diverse than samples of American college students (Buhrmester, Kwang, & Gosling, 2011; Casler, Bickel, & Hackett, 2013).”
An Analysis of Data Quality: Professional Panels, Student Subject Pools, and Amazon's Mechanical Turk (2017, background): “…student and professional panel samples in domains outside of advertising is increasing (e.g., Bartneck et al. 2015; Berinsky, Huber, and Lenz 2012; Casler, Bickel, and Hackett 2013; Clifford, Jewell, and Waggoner 2015; Goodman, Cryder, and Cheema 2013; Heen, Lieberman, and Miethe 2014; Hamby and…”
Coronavirus Fears and Macroeconomic Expectations (2020, positive): “1Mechanical Turk allows for recruitment of subject pools that are more nationally representative than typical convenience samples, making it a popular choice for social science experiments (Berinsky et al., 2012; Casler et al., 2013; Levay et al., 2016).”
Demographics and Dynamics of Mechanical Turk Workers (2018, result): “, college students) occurs despite the MTurk workers being significantly more socioeconomically and ethnically diverse than test participants recruited using other methods [6].”
Estimating the Reproducibility of Experimental Philosophy (2018, background): “Thus, it seems that most original findings based on convenience samples such as pedestrians or university students could be generalized to online samples (Casler et al. 2013).”