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Garbage in, garbage out? : do machine learning applicati..:

, In: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency,

Geiger, R. Stuart ; Yu, Kevin ; Yang, Yanlai... - p. 325-336 , 2020

Link: https://dl.acm.org/doi/10.1145/3351095.3372862

RT 
T1 <cTitle>Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency</cTitle>: T1 <Title>Garbage in, garbage out?				: do machine learning application papers in social computing report where human-labeled training data comes from?</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3372862&Exemplar=1&LAN=DE
				
A1 Geiger, R. Stuart
A1 Yu, Kevin
A1 Yang, Yanlai
A1 Dai, Mindy
A1 Qiu, Jie
A1 Tang, Rebekah
A1 Huang, Jenny
PB ACM
YR 2020
K1 content analysis
K1 data labeling
K1 human annotation
K1 machine learning
K1 meta-research
K1 research integrity
K1 training data
K1 Information systems
K1 Information retrieval
K1 Document representation
K1 Content analysis and feature selection
K1 Social and professional topics
K1 Professional topics
K1 Management of computing and information systems
K1 Project and people management
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Supervised learning
K1 Supervised learning by classification
SP 325
OP 336
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3351095.3372862
DO https://dl.acm.org/doi/10.1145/3351095.3372862
SF ELIB - SuUB Bremen

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