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Effect of Cognitive Abilities on Crowdsourcing Task Performance

Abstract : Matching crowd workers to suitable tasks is highly desirable as it can enhance task performance, reduce the cost for requesters, and increase worker satisfaction. In this paper, we propose a method that considers workers’ cognitive ability to predict their suitability for a wide range of crowdsourcing tasks. We measure cognitive ability via fast-paced online cognitive tests with a combined average duration of 6.2 min. We then demonstrate that our proposed method can effectively assign or recommend workers to five different popular crowd tasks: Classification, Counting, Proofreading, Sentiment Analysis, and Transcription. Using our approach we demonstrate a significant improvement in the expected overall task accuracy. While previous methods require access to worker history or demographics, our work offers a quick and accurate way to determine which workers are more suitable for which tasks.
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Contributor : Hal Ifip <>
Submitted on : Thursday, April 16, 2020 - 2:30:13 PM
Last modification on : Thursday, April 16, 2020 - 3:23:10 PM


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Danula Hettiachchi, Niels Berkel, Simo Hosio, Vassilis Kostakos, Jorge Goncalves. Effect of Cognitive Abilities on Crowdsourcing Task Performance. 17th IFIP Conference on Human-Computer Interaction (INTERACT), Sep 2019, Paphos, Cyprus. pp.442-464, ⟨10.1007/978-3-030-29381-9_28⟩. ⟨hal-02544572⟩



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