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Putting User Reputation on the Map: Unsupervised Quality Control for Crowdsourced Historical Data

, , , and . 2nd ACM SIGSPATIAL Workshop on Geospatial Humanities, (2018)

Abstract

In this paper we propose a novel method for quality assessment of crowdsourced data. It computes user reputation scores without requiring ground truth; instead, it is based on the consistency among users. In this pilot study, we perform some explorative data analysis on two real crowdsourcing projects by the New York Public Library: extracting building footprints as polygons from historical insurance atlases, and geolocating historical photographs. We show that the computed reputation scores are plausible and furthermore provide insight into user behavior.

Links and resources

DOI:
10.1145/3282933.3282937
BibTeX key:
Barz18:Reputation
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