Published:
2013-11-10
Proceedings:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 1
Volume
Issue:
Vol. 1 (2013): First AAAI Conference on Human Computation and Crowdsourcing
Track:
Works in Progress
Downloads:
Abstract:
This paper describes an approach to improving the reliability of a crowdsourced labeling task for which there is no objective right answer. Our approach focuses on three contingent elements of the labeling task: data quality, worker reliability, and task design. We describe how we developed and applied this framework to the task of labeling tweets according to their interestingness. We use in-task CAPTCHAs to identify unreliable workers, and measure inter-rater agreement to decide whether subtasks have objective or merely subjective answers.
DOI:
10.1609/hcomp.v1i1.13097
HCOMP
Vol. 1 (2013): First AAAI Conference on Human Computation and Crowdsourcing
ISBN 978-1-57735-607-3