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China, DIME, and innovative deterrence methodology: How authoritarian states react to deterrence activities through information

Published online by Cambridge University Press:  25 November 2025

Scott Fisher
Affiliation:
Security Studies Department, New Jersey City University (NJCU), Jersey City, NJ, USA
Graig R. Klein*
Affiliation:
Institute of Security & Global Affairs, Leiden University, Leiden, Netherlands
Juris Pupcenoks
Affiliation:
Political Science Department, Marist University, Poughkeepsie, NY, USA
Juste Codjo
Affiliation:
Security Studies Department, New Jersey City University (NJCU), Jersey City, NJ, USA
*
Corresponding author: Graig R. Klein; Email: g.r.e.klein@fgga.leidenuniv.nl
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Abstract

Contemporary deterrence scholarship remains disproportionately focused on military instruments, often neglecting the strategic utility of diplomacy, information, and economic statecraft. Our study addresses this imbalance through a new methodology for analysing how authoritarian states respond to the range of foreign policy tools: diplomatic, information, military, and economic (the DIME framework). Using a state’s propaganda, official statements, and media (POSM) to capture target states’ reactions to adversarial DIME actions, we offer an innovative analytical framework that enhances understanding of deterrence dynamics beyond the military sphere. Within the framework, we use computational text analysis, statistical analysis, and data visualisation to create a replicable process for analysing POSM big data. Applying this methodology to a case study of China, we find that Beijing’s POSM-based responses to information tools – such as public criticism of censorship and information control by NGOs – are more negative than to diplomatic, military, or economic tools. Our methodology contributes to deterrence theory and policy through its insight into non-military effects and by offering a scalable process for empirical analysis ripe for AI implementation. For policymakers, our process and findings hold implications for crafting more effective and sustainable deterrence strategies in an increasingly complex international security environment.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The British International Studies Association.
Figure 0

Table 1 DIME search terms.

Figure 1

Figure 1. MOFA baseline sentiment using AFINN.

Figure 2

Figure 2. MOFA baseline sentiment using Bing.

Figure 3

Figure 3. Global Times baseline sentiment using AFINN.

Figure 4

Figure 4. 4 Global Times baseline sentiment using Bing.

Figure 5

Figure 5. People’s Daily baseline sentiment using AFINN.

Figure 6

Figure 6. People’s Daily baseline sentiment using Bing.

Figure 7

Figure 7. Number and sentiment of People’s Daily articles referencing UN [United Nations] Human Rights, 2007–2022.

Figure 8

Figure 8. Number and sentiment of MOFA articles referencing UN special rapporteur, 2017–2022.

Figure 9

Figure 9. Number and sentiment of Global Times articles referencing UN special rapporteur, 2009–2022.

Figure 10

Figure 10. Number and sentiment of People’s Daily articles referencing UN special rapporteur, 2007–2022.

Figure 11

Figure 11. Number and sentiment of Global Times articles referencing Reporters Without Borders, 2009–2022.

Figure 12

Figure 12. Number and sentiment of People’s Daily articles referencing Reporters Without Borders, 2007–2022.

Figure 13

Figure 13. Number and sentiment of People’s Daily articles referencing Human Rights Watch, 2007–2022.

Figure 14

Figure 14. Number and sentiment of Global Times articles referencing Ulchi, 2009–2022.

Figure 15

Figure 15. Number and sentiment of People’s Daily articles referencing Ulchi, 2007–2022.

Figure 16

Figure 16. Number and sentiment of Global Times articles referencing Han Kuang, 2009–2022.

Figure 17

Figure 17. Number and sentiment of People’s Daily articles referencing Han Kuang, 2007–2022.

Figure 18

Figure 18. Number and sentiment of Global Times articles referencing Huawei, 2009–2022.

Figure 19

Figure 19. Number and sentiment of People’s Daily articles referencing Huawei, 2007–2022.

Figure 20

Figure 20. Number and sentiment of MOFA articles referencing Huawei, 2014–2022.

Figure 21

Figure 21. Number and sentiment of Global Times articles referencing section 889 (Huawei Sanction).

Figure 22

Figure 22. Number and sentiment of Global Times articles referencing economic sanctions, 2009–2022.

Figure 23

Figure 23. Number and sentiment of People’s Daily articles referencing economic sanctions, 2007–2022.

Figure 24

Figure 24. Number and sentiment of MOFA articles referencing economic sanctions, 2014–2022.

Figure 25

Table 2 Two sample t-test results (if only specific DIME tool is identified in article, comparing DIME & non-DIME articles).

Figure 26

Table 3 Summary statistics of standardised sample, 9 April 2009–31 December 2022.

Figure 27

Table 4 Two sample t-test results (if only specific DIME tool is identified in article, comparing US & non-US articles).

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Table 5 Two sample t-test results (if only specific DIME tool is identified in article).

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