Spammer Detection Based on Task Completion Time Variation in Crowdsourcing

by Ayato Watanabe, Keishi Tajima


Many existing spammer detection methods uses dependency between workers' answers and the true answers. These methods may regard a diligent but low-skilled worker as a spammer. Our method uses correlation between workers' task completion time and the difficulty of the tasks. Our experimental result suggests that this approach is potentially useful, but the selection of tasks seems a key for success.

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human computation; worker quality
Published in Proc. of HMData (collocated with IEEE BigData), pp.3568-3570, 2021

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