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Conference Papers Year : 2019

Effect of Cognitive Abilities on Crowdsourcing Task Performance

Danula Hettiachchi
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Niels Van Berkel
Simo Hosio
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Vassilis Kostakos
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Jorge Goncalves
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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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Dates and versions

hal-02544572 , version 1 (16-04-2020)





Danula Hettiachchi, Niels Van 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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