The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Crowdsourcing user studies with Mechanical Turk
Abstract
User studies are important for many aspects of the design process and involve techniques ranging from informal surveys to rigorous laboratory studies. However, the costs involved in engaging users often requires practitioners to trade off between sample size, time requirements, and monetary costs. Micro-task markets, such as Amazon's Mechanical Turk, offer a potential paradigm for engaging a large number of users for low time and monetary costs. Here we investigate the utility of a micro-task market for collecting user measurements, and discuss design considerations for developing remote micro user evaluation tasks. Although micro-task markets have great potential for rapidly collecting user measurements at low costs, we found that special care is needed in formulating tasks in order to harness the capabilities of the approach.
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Cites
Coase's penguin, or, linux and “the nature of the firm”
Benkler, Y. (2002) · The Yale Law Journal · doi:10.2307/1562247 · Cited by 1,572
Viégas, F. B., Wattenberg, M., & McKeon, M. M. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-73257-0_49 · Cited by 195
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Hutto, C., & Gilbert, E. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14550 · Cited by 6,087
Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk
Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012) · Political Analysis · doi:10.1093/pan/mpr057 · Cited by 4,008
Conducting behavioral research on Amazon’s Mechanical Turk
Mason, W., & Suri, S. (2012) · Behavior Research Methods · doi:10.3758/s13428-011-0124-6 · Cited by 3,172
Inside the Turk: Understanding Mechanical Turk as a Participant Pool
Paolacci, G., & Chandler, J. (2014) · Current Directions in Psychological Science · doi:10.1177/0963721414531598 · Cited by 2,136
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
Snow, R., O'Connor, B., Jurafsky, D., & Ng, A. Y. (2008) · Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08 · doi:10.3115/1613715.1613751 · Cited by 1,887
Metadata
- Authors
- Kittur, A., Chi, E. H., & Suh, B.
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2008-04-06
- Pages
- 453-456
- OpenAlex
- W2151401338
- Cited by
- 1,923
- References
- 2
- FWCI
- 88.96
- Type
- conference paper
- Language
- en
- Open access
- closed
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