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Cited by 973

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Quality management on Amazon Mechanical Turk

Ipeirotis, Panagiotis G., Provost, Foster, Wang, Jing·2010·Proceedings of the ACM SIGKDD Workshop on Human Computation

Abstract

Crowdsourcing services, such as Amazon Mechanical Turk, allow for easy distribution of small tasks to a large number of workers. Unfortunately, since manually verifying the quality of the submitted results is hard, malicious workers often take advantage of the verification difficulty and submit answers of low quality. Currently, most requesters rely on redundancy to identify the correct answers. However, redundancy is not a panacea. Massive redundancy is expensive, increasing significantly the cost of crowdsourced solutions. Therefore, we need techniques that will accurately estimate the quality of the workers, allowing for the rejection and blocking of the low-performing workers and spammers.

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Metadata

Authors
Ipeirotis, P. G., Provost, F., & Wang, J.
Venue
Proceedings of the ACM SIGKDD Workshop on Human Computation
Publisher
ACM
Published
2010-07-25
Pages
64-67
OpenAlex
W2098865355
Cited by
973
References
1
FWCI
63.06
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Quality management on Amazon Mechanical Turk. https://app.cochat.ai/papers/10.1145/1837885.1837906
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Ipeirotis, P. G., Provost, F., & Wang, J. (2010). Quality management on Amazon Mechanical Turk. Proceedings of the ACM SIGKDD Workshop on Human Computation. https://doi.org/10.1145/1837885.1837906

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