The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Demographics and Dynamics of Mechanical Turk Workers
Abstract
We present an analysis of the population dynamics and demographics of Amazon Mechanical Turk workers based on the results of the survey that we conducted over a period of 28 months, with more than 85K responses from 40K unique participants. The demographics survey is ongoing (as of November 2017), and the results are available at http://demographics.mturk-tracker.com: we provide an API for researchers to download the survey data. We use techniques from the field of ecology, in particular, the capture-recapture technique, to understand the size and dynamics of the underlying population. We also demonstrate how to model and account for the inherent selection biases in such surveys. Our results indicate that there are more than 100K workers available in Amazon»s crowdsourcing platform, the participation of the workers in the platform follows a heavy-tailed distribution, and at any given time there are more than 2K active workers. We also show that the half-life of a worker on the platform is around 12-18 months and that the rate of arrival of new workers balances the rate of departures, keeping the overall worker population relatively stable. Finally, we demonstrate how we can estimate the biases of different demographics to participate in the survey tasks, and show how to correct such biases. Our methodology is generic and can be applied to any platform where we are interested in understanding the dynamics and demographics of the underlying user population.
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Cites
Cribari-Neto, F., & Zeileis, A. (2010) · Journal of Statistical Software · doi:10.18637/jss.v034.i02 · Cited by 2,505
A better lemon squeezer? maximum-likelihood regression with beta-distributed dependent variables.
Smithson, M., & Verkuilen, J. (2006) · Psychological Methods · doi:10.1037/1082-989x.11.1.54 · Cited by 1,788
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“, college students) occurs despite the MTurk workers being significantly more socioeconomically and ethnically diverse than test participants recruited using other methods [6].”
ResultConducting Clinical Research Using Crowdsourced Convenience Samples
Chandler, J., & Shapiro, D. (2016) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-021815-093623 · Cited by 1,072
The average laboratory samples a population of 7,300 Amazon Mechanical Turk workers
Stewart, N., Ungemach, C., Harris, A. J. L., Bartels, D. M., Newell, B. R., Paolacci, G., & Chandler, J. (2015) · Judgment and Decision Making · doi:10.1017/s1930297500005611 · Cited by 304 · cited 7×
“[34]) is not a solution, as even in the simple two-occasion model (where we cannot eliminate any worker), we still observe significant underestimates.”
BackgroundMethodResultInfluentialMiller, J. D., Crowe, M., Weiss, B., Maples-Keller, J. L., & Lynam, D. R. (2017) · Personality Disorders Theory Research and Treatment · doi:10.1037/per0000191 · Cited by 179
Cited by
Online panels in social science research: Expanding sampling methods beyond Mechanical Turk
Chandler, J., Rosenzweig, C., Moss, A. J., Robinson, J., & Litman, L. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01273-7 · Cited by 668
StereoSet: Measuring stereotypical bias in pretrained language models
Nadeem, M., Bethke, A., & Reddy, S. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · doi:10.18653/v1/2021.acl-long.416 · Cited by 643
Yang, K., Qinami, K., Fei-Fei, L., Deng, J., & Russakovsky, O. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency · doi:10.1145/3351095.3375709 · Cited by 254
Evaluation of Text Generation: A Survey
Celikyilmaz, A., Clark, E., & Gao, J. (2020) · arXiv · doi:10.48550/arxiv.2006.14799 · Cited by 207
Micro-work, artificial intelligence and the automotive industry
Tubaro, P., & Casilli, A. A. (2019) · Journal of Industrial and Business Economics · doi:10.1007/s40812-019-00121-1 · Cited by 122
Metadata
- Authors
- Difallah, D., Filatova, E., & Ipeirotis, P.
- Venue
- Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining
- Publisher
- ACM
- Published
- 2018-02-02
- Pages
- 135-143
- OpenAlex
- W2783946743
- Cited by
- 501
- References
- 6
- FWCI
- 77.50
- Type
- conference paper
- Language
- en
- Open access
- closed
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