CrowdHub: Extending crowdsourcing platforms for the controlled evaluation of tasks designs
September 06, 2019 Β· Declared Dead Β· π arXiv.org
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Authors
Jorge RamΓrez, Simone Degiacomi, Davide Zanella, Marcos Baez, Fabio Casati, Boualem Benatallah
arXiv ID
1909.02800
Category
cs.HC: Human-Computer Interaction
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We present CrowdHub, a tool for running systematic evaluations of task designs on top of crowdsourcing platforms. The goal is to support the evaluation process, avoiding potential experimental biases that, according to our empirical studies, can amount to 38% loss in the utility of the collected dataset in uncontrolled settings. Using CrowdHub, researchers can map their experimental design and automate the complex process of managing task execution over time while controlling for returning workers and crowd demographics, thus reducing bias, increasing utility of collected data, and making more efficient use of a limited pool of subjects.
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