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Diversity in Big Data: A Review
Journal article   Open access   Peer reviewed

Diversity in Big Data: A Review

Marina Drosou, H V Jagadish, Evaggelia Pitoura and Julia Stoyanovich
Big data, v 5(2), pp 73-84
Jun 2017
PMID: 28632443
url
https://doi.org/10.1089/big.2016.0054View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze) Restricted

Abstract

Crowdsourcing Data Interpretation, Statistical Empirical Research Models, Statistical Personnel Selection Algorithms
Big data technology offers unprecedented opportunities to society as a whole and also to its individual members. At the same time, this technology poses significant risks to those it overlooks. In this article, we give an overview of recent technical work on diversity, particularly in selection tasks, discuss connections between diversity and fairness, and identify promising directions for future work that will position diversity as an important component of a data-responsible society. We argue that diversity should come to the forefront of our discourse, for reasons that are both ethical-to mitigate the risks of exclusion-and utilitarian, to enable more powerful, accurate, and engaging data analysis and use.

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Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Interdisciplinary Applications
Computer Science, Theory & Methods
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