Abstract

 Appropriate task routing and assignment is an important, but often overlooked, element in crowdsourcing research and practice. In this paper, we explore and evaluate a mechanism that can enable matching crowdsourcing tasks to suitable crowd-workers based on their cognitive abilities. We measure participants’ visual and fluency cognitive abilities with the well-established Kit of Factor-Referenced Cognitive Test, and measure crowdsourcing performance with our own set of developed tasks. Our results indicate that participants’ cognitive abilities correlate well with their crowdsourcing performance. We also built two predictive models (beta and linear regression) for crowdsourcing task performance based on the performance on cognitive tests as explanatory variables. The model results suggest that it is feasible to predict crowdsourcing performance based on cognitive abilities. Finally, we discuss the benefits and challenges of leveraging workers’ cognitive abilities to improve task routing and assignment in crowdsourcing environments.

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The different versions of the original document can be found in:

http://dx.doi.org/10.1145/3041021.3055128 under the license http://creativecommons.org/licenses/by/4.0/
https://www.zora.uzh.ch/id/eprint/144125/1/WebS0163-goncalves.pdf,
http://jultika.oulu.fi/files/nbnfi-fe2018052524635.pdf,
https://dl.acm.org/citation.cfm?doid=3041021.3055128,
https://core.ac.uk/display/154256116,
https://findanexpert.unimelb.edu.au/scholarlywork/1201956-task-routing-and-assignment-in-crowdsourcing-based-on-cognitive-abilities,
https://doi.acm.org/10.1145/3041021.3055128,
http://jultika.oulu.fi/Record/nbnfi-fe2018052524635,
https://doi.org/10.1145/3041021.3055128,
https://dl.acm.org/citation.cfm?id=3055128,
https://people.eng.unimelb.edu.au/vkostakos/publications.php?key=RN11995,
http://dblp.uni-trier.de/db/conf/www/www2017c.html#GoncalvesFHKB17,
https://academic.microsoft.com/#/detail/2613162388 under the license http://www.acm.org/publications/policies/copyright_policy#Background



DOIS: 10.1145/3041021.3055128 10.5167/uzh-144125

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Published on 01/01/2017

Volume 2017, 2017
DOI: 10.1145/3041021.3055128
Licence: Other

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