89 citations · 279 across the 9 of their papers we have counts for
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cs.CY2019
Garbage In, Garbage Out? Do Machine Learning Application Papers in Social Computing Report Where Human-Labeled Training Data Comes From?
R. Stuart Geiger, Kevin Yu, Yanlai Yang +4
Many machine learning projects for new application areas involve teams of humans who label data for a particular purpose, from hiring crowdworkers to the paper's authors labeling t…
cs.HC2019★ 3 cited
The Rise and Fall of the Note: Changing Paper Lengths in ACM CSCW, 2000-2018
R. Stuart Geiger
In this note, I quantitatively examine various trends in the lengths of published papers in ACM CSCW from 2000-2018, focusing on several major transitions in editorial and reviewin…
cs.HC2019★ 25 cited
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia
Aaron Halfaker, R. Stuart Geiger
Algorithmic systems---from rule-based bots to machine learning classifiers---have a long history of supporting the essential work of content moderation and other curation work in p…