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How ethics combine with big data: a bibliometric analysis

Author

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  • Marta Kuc-Czarnecka

    (Gdansk University of Technology)

  • Magdalena Olczyk

    (Gdansk University of Technology)

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.

Suggested Citation

  • Marta Kuc-Czarnecka & Magdalena Olczyk, 2020. "How ethics combine with big data: a bibliometric analysis," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-9, December.
    • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-00638-0
    DOI: 10.1057/s41599-020-00638-0
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    References listed on IDEAS

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    1. Marina Johnson & Rashmi Jain & Peggy Brennan-Tonetta & Ethne Swartz & Deborah Silver & Jessica Paolini & Stanislav Mamonov & Chelsey Hill, 2021. "Impact of Big Data and Artificial Intelligence on Industry: Developing a Workforce Roadmap for a Data Driven Economy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 22(3), pages 197-217, September.
    2. Abderahman Rejeb & Karim Rejeb & Andrea Appolloni & Mohammad Iranmanesh & Horst Treiblmaier & Sandeep Jagtap, 2022. "Exploring Food Supply Chain Trends in the COVID-19 Era: A Bibliometric Review," Sustainability, MDPI, vol. 14(19), pages 1-33, September.
    3. Aroa Costa-Feito & Ana M. González-Fernández & Carmen Rodríguez-Santos & Miguel Cervantes-Blanco, 2023. "Electroencephalography in consumer behaviour and marketing: a science mapping approach," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.

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