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How ethics combine with big data: a bibliometric analysis

Abstract

The term Big Data is becoming increasingly widespread throughout the world, and its use is no longer limited to the IT industry, quantitative scientific research, and entrepreneurship, but entered as well everyday media and conversations. The prevalence of Big Data is simply a result of its usefulness in searching, downloading, collecting and processing massive datasets. It is therefore not surprising that the number of scientific articles devoted to this issue is increasing. However, the vast majority of research papers deal with purely technical matters. Yet, large datasets coupled with complex analytical algorithms pose the risk of non-transparency, unfairness, e.g., racial or class bias, cherry-picking of data, or even intentional misleading of public opinion, including policymakers, for example by tampering with the electoral process in the context of ‘cyberwars’. Thus, this work implements a bibliometric analysis to investigate the development of ethical concerns in the field of Big Data. The investigation covers articles obtained from the Web of Science Core Collection Database (WoS) published between 1900 and July 2020. A sample size of 892 research papers was evaluated using HistCite and VOSviewer software. The results of this investigation shed light on the evolution of the junction of two concepts: ethics and Big Data. In particular, the study revealed the following array of findings: the topic is relatively poorly represented in the scientific literature with the relatively slow growth of interest. In addition, ethical issues in Big Data are discussed mainly in the field of health and technology.

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
Humanities & Social Sciences Communications no. 7, pages 1 - 9,
ISSN:
Language:
English
Publication year:
2020
Bibliographic description:
Kuc-Czarnecka M., Olczyk M.: How ethics combine with big data: a bibliometric analysis// Humanities & Social Sciences Communications -Vol. 7, (2020), s.1-9
DOI:
Digital Object Identifier (open in new tab) 10.1057/s41599-020-00638-0
Verified by:
Gdańsk University of Technology

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