Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)

Big Data: Quasi-public Goods Correlating with National Security and Social Stability

Authors
Yunlong Zhang1, *, Jiangbo Wang2, Yue Liu3, Wuji Yan4
1School of Art and Communication, Beijing Normal University Zhuhai Campus, Zhuhai, 519000, Guangdong, China
2Goldsmiths, University of London, London, SE14 6NW, UK
3Donald P. Bellisario College of Communications, Penn State University, State College, PA, 16803, USA
4Beijing No.4 High School International Campus, Beijing, 100032, China
*Corresponding author. Email: zhangyunlong0129@126.com
Corresponding Author
Yunlong Zhang
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-064-0_2How to use a DOI?
Keywords
Quasi-Public Goods; National Security; DiDi Chuxing; Cambridge analytics
Abstract

In the Internet era, data is occupying an increasingly important position, and some important data may even affect the country. More and more people demand that big data correlating with national security and social stability be treated as public goods which hold the characteristics of non-excludable and non-rivalrous. However, due to the economic attribute of big data, we proposes that this type of big data is excludable and non-rivalrous, and should be treated as quasi-public goods. To support this point of view, we quoted two examples, DiDi Chuxing and Cambridge analytics, and give solutions respectively. We believes that the government, as a public service provider, should supervises the use of big data rather than the content of big data. It not only protects the private rights of enterprises to data, but also avoids big data leaks that threaten national security.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-064-0_2
ISSN
2589-4900
DOI
10.2991/978-94-6463-064-0_2How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Yunlong Zhang
AU  - Jiangbo Wang
AU  - Yue Liu
AU  - Wuji Yan
PY  - 2022
DA  - 2022/12/27
TI  - Big Data: Quasi-public Goods Correlating with National Security and Social Stability
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 4
EP  - 12
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_2
DO  - 10.2991/978-94-6463-064-0_2
ID  - Zhang2022
ER  -