Approximating the wisdom of the crowd

Ertekin Bolelli, Şeyda
Hirsh, Haym
Rudin, Cynthia
The problem of “approximating the crowd” is that of estimating the crowd’s majority opinion by querying only a subset of it. Algorithms that approximate the crowd can intelligently stretch a limited budget for a crowdsourcing task. We present an algorithm, “CrowdSense,” that works in an online fashion to dynamically sample subsets of labelers based on an exploration/exploitation criterion. The algorithm produces a weighted combination of the labelers’ votes that approximates the crowd’s opinion.
Citation Formats
Ş. Ertekin Bolelli, H. Hirsh, and C. Rudin, “Approximating the wisdom of the crowd,” presented at the NIPS 2011 Second Workshop on Computational Social Science and the Wisdom of Crowds (17 Aralık 2011), Granada, Nikaragua, 2011, Accessed: 00, 2021. [Online]. Available: