Paintings, Not Noise—The Role of Presentation Sequence in Labeling
Merlin Knaeble,
Mario Nadj,
Alexander Maedche
Abstract:Labeling is critical in creating training datasets for supervised machine learning, and is a common form of crowd work heteromation. It typically requires manual labor, is badly compensated and not infrequently bores the workers involved. Although task variety is known to drive human autonomy and intrinsic motivation, there is little research in this regard in the labeling context. Against this backdrop, we manipulate the presentation sequence of a labeling task in an online experiment and use the theoretical … Show more
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