Bibliometric analysis is a commonly used tool to assess scientific collaborations within the researchers, community, institution, regions and countries. The analysis of publication records can provide a wealth of information about scientific collaboration, including the number of publications, the impact of the publications, and the areas of research where collaborations are most common. By providing detailed information on the patterns and trends in scientific collaboration, these tools can help to inform policy decisions and promote the development of effective strategies to support and enhance scientific collaborations between countries. This study aimed to analyze and visualize the scientific collaboration between Japan and Russia, using bibliometric analysis of collaborative publications from the Web of Science (WoS) database. The analysis utilized the bibliometrix package within the R statistical program. The analysis covered a period of two decades, from 2000 to 2021. The results showed a slight decrease in co-authored publications, with an annual growth rate of −1.26%. The keywords and thematic trends analysis confirmed that physics is the most co-authored field between the two countries. The study also analyzed the collaboration network and research funding sources. Overall, the study provides valuable insights into the current state of scientific collaboration between Japan and Russia. The study also highlights the importance of research funding sources in promoting and sustaining scientific cooperation between countries. The analysis suggests that more efforts in government funding are needed to increase collaboration between the two countries in various fields.

1. Abbas, A. F., Jusoh, A., Mas’od, A., et al. (2022). Bibliometrix analysis of information sharing in social media. Cogent Business and Management, 9(1). https://doi.org/10.1080/23311975.2021.2016556
2. Abdullah, K. H. (2021). Publication Trends and Thematic Evolution of Safety Motivation Research: A Bibliometric Review. Proceedings on Engineering Sciences, 3(2), 181–192. https://doi.org/10.24874/PES03.02.006
3. Abdullah, K. H., Roslan, M. F., Ishak, N. S., et al. (2023). Unearthing Hidden Research Opportunities Through Bibliometric Analysis: A Review. Asian Journal of Research in Education and Social Sciences, 5(1), 251–262. https://doi.org/10.55057/ajress.2023.5.1.23
4. Allakhverdov, A. (2018). Head of controversial agency becomes Russian minister for science and higher education. Science. https://doi.org/10.1126/SCIENCE.AAU2276
5. Aref, S., Friggens, D., & Hendy, S. (2018). Analysing scientific collaborations of New Zealand institutions using Scopus bibliometric data. ACM International Conference Proceeding Series, 1–10. https://doi.org/10.1145/3167918.3167920
6. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
7. Boiarskii, B. (2022). Agricultural sciences publication activity in Russia and the impact of the national project “science.” A bibliometric analysis. Open Agriculture, 7(1), 889–898. https://doi.org/10.1515/OPAG-2022-0070/MACHINEREADABLECITATION/RIS
8. Briner, R. B., & Denyer, D. (2012). Systematic Review and Evidence Synthesis as a Practice and Scholarship Tool. In: The Oxford Handbook of Evidence-Based Management. Oxford Academic. https://doi.org/10.1093/oxfordhb/9780199763986.013.0007
9. Büyükkidik, S. (2022). A Bibliometric Analysis: A Tutorial for the Bibliometrix Package in R Using IRT Literature. Journal of Measurement and Evaluation in Education and Psychology, 13(3). https://doi.org/10.21031/EPOD.1069307
10. Cañas-Guerrero, I., Mazarrón, F. R., Pou-Merina, A., et al. (2013). Bibliometric analysis of research activity in the “Agronomy” category from the Web of Science, 1997–2011. European Journal of Agronomy, 50, 19–28. https://doi.org/10.1016/J.EJA.2013.05.002
11. Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002
12. Dervis, H. (2019). Bibliometric analysis using bibliometrix an R package. Journal of Scientometric Research, 8(3), 156–160. https://doi.org/10.5530/JSCIRES.8.3.32
13. Dezhina, I. (2020). Science and Innovations in Russia in 2019. SSRN Electronic Journal, 484–508. https://doi.org/10.2139/ssrn.3449220
14. Donthu, N., Kumar, S., Mukherjee, D., et al. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133. https://doi.org/10.1016/j.jbusres.2021.04.070
15. e-ASIA JRP. (n.d.). Member Organizations. Available online: https://www.the-easia.org/jrp/members.html (accessed on 12 December 2023).
16. Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105(3), 1809–1831. https://doi.org/10.1007/S11192-015-1645-Z/TABLES/9
17. Fu, Y. C., Marques, M., Tseng, Y. H., et al. (2022). An evolving international research collaboration network: spatial and thematic developments in co-authored higher education research, 1998–2018. Scientometrics, 127(3), 1403–1429. https://doi.org/10.1007/S11192-021-04200-W/TABLES/4
18. Fung, H. N., & Wong, C. Y. (2017). Scientific collaboration in indigenous knowledge in context: Insights from publication and co-publication network analysis. Technological Forecasting and Social Change, 117, 57–69. https://doi.org/10.1016/j.techfore.2017.01.009
19. Garfield, E. (1990). KeyWords Plus: ISI’s Breakthrough Retrieval Method. Part 1. Expanding Your Searching Power. Current Contents on Diskette, 32(32), 3–7.
20. Gautam, P. (2016). Comparative analysis of scientific publications of research entities using multiple disciplinary classifications. In: Proceedings of the 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016. https://doi.org/10.1109/IIAI-AAI.2016.117
21. Gautam, P. (2017). An overview of the Web of Science record of scientific publications (2004–2013) from Nepal: focus on disciplinary diversity and international collaboration. Scientometrics, 113(3), 1245–1267. https://doi.org/10.1007/s11192-017-2538-0
22. Guleria, D., & Kaur, G. (2021). Bibliometric analysis of ecopreneurship using VOSviewer and RStudio Bibliometrix, 1989–2019. Library Hi Tech, 39(4), 1001–1024. https://doi.org/10.1108/LHT-09-2020-0218/FULL/XML
23. JSPS. (2024). International Academic Collaborations. Available online: https://www.jsps.go.jp/file/storage/j-kokusai/IC_leaflet_en.pdf (accessed on 3 January 2024).
24. Kholidah, H., Hijriah, H. Y., Mawardi, I., et al. (2022). A Bibliometric mapping of peer-to-peer lending research based on economic and business perspective. Heliyon, 8(11). https://doi.org/10.1016/j.heliyon.2022.e11512
25. Lyude, A., Boiarskii, B., & Hasegawa, H. (2021). International joint research: Current situation and challenges for the Japan-Russia collaboration in the field of agriculture. IOP Conference Series: Earth and Environmental Science, 677(5). https://doi.org/10.1088/1755-1315/677/5/052114
26. Ministry of Science and Higher Education of the Russian Federation. (2019). National Project “Science.” Available online: https://riep.ru/upload/iblock/7c0/7c05bb11361d839a83251cab40066a95.pdf (accessed on 3 January 2024).
27. Moed, H. F., Markusova, V., & Akoev, M. (2018). Trends in Russian research output indexed in Scopus and Web of Science. Scientometrics, 116(2), 1153–1180. https://doi.org/10.1007/s11192-018-2769-8
28. MOFA. (2000). Agreement between the Government of the Russian Federation and the Government of Japan on scientific and technical cooperation. Available online: https://www.mofa.go.jp/mofaj/gaiko/treaty/pdfs/A-H12-1705.pdf (accessed on 3 January 2024).
29. MOFA: Japan’s Assistance Programs for Russia. (2001). Available online: https://www.mofa.go.jp/region/europe/russia/assistance/index.html (accessed on 3 January 2024).
30. Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional de La Información, 29(1), 1–20. https://doi.org/10.3145/EPI.2020.ENE.03
31. Mulay, P., Joshi, R., & Chaudhari, A. (2020). Distributed Incremental Clustering Algorithms: A Bibliometric and Word-Cloud Review Analysis. Science and Technology Libraries, 39(3). https://doi.org/10.1080/0194262X.2020.1775163
32. Patil, R. R., Kumar, S., Rani, R., et al. (2023). A Bibliometric and Word Cloud Analysis on the Role of the Internet of Things in Agricultural Plant Disease Detection. Applied System Innovation, 6(1). https://doi.org/10.3390/asi6010027
33. Russian Science Foundation. (2017). Russia and Japan to build stronger science bonds. Available online: https://rscf.ru/en/news/en-57/russia_and_japan_to_build_stronger_science_bonds/ (accessed on 3 January 2024).
34. Strategic International Collaborative Research Program. (2019). Bilateral cooperation, Russia. Available online: https://www.jst.go.jp/inter/english/program_e/sicorp_e/russia.html (accessed on 3 January 2024).
35. The Embassy of the Russian Federation in Japan. (2021). Science and technology cooperation. Available online: https://oldtokyo.mid.ru/web/tokyo-en/science-and-technology-cooperation (accessed on 3 January 2024).
36. Tseng, Y. H., & Tsay, M. Y. (2013). Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR. Scientometrics, 95(2), 503–528. https://doi.org/10.1007/S11192-013-0964-1
37. Yeh, S. C., Hsieh, Y. L., Yu, H. C., & Tseng, Y. H. (2022). The Trends and Content of Research Related to the Sustainable Development Goals: A Systemic Review. Applied Sciences, 12(13), 6820. https://doi.org/10.3390/APP12136820