Abstract
Co-authored publications can bring positive results for those who participate, such as gaining additional expertise, accessing more funding or increasing the publication impact. China, the European Union, and the United States have been collaborating between each other throughout the years in the field of Computer Science. These collaborations varied over time, as well as they impacted the regions in different ways. In this paper, we collected the publications from these territories across 31 years on the topic of Computer Science and studied them focusing on how the regions have approached co-authorship. In particular, we have analyzed the number of collaborations during that period, the impact of those papers measured as the number of citations, and the topics that have been researched. We conclude that China’s focus on Computer Science fields has led it to be the most productive region in recent years; plus, it has benefited from the American and European reputation, by increasing its citation rates when collaborating with them. On the other hand, the EU and the US have benefited from Chinese interest in computer science, increasing the number of publications together.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
The proportion of internationally co-authored scientific papers has significantly increased since the turn of the century, representing a growing share of all scientific cooperation, while the rate of the in-home collaboration has been proportionally falling (Adams, 2013; Wagner et al., 2015).
This growth is mainly attributed to emerging nations, most notably China, that have amplified their engagement in global scientific endeavors, partly by doubling their investment in research and development. As a result, they are progressively more inclined to collaborate as partners in internationally authored scientific publications (Wagner et al., 2015). International collaboration can in general bring positive results to the countries that participate. For example, papers co-authored by individuals from multiple nations receive higher citation rates compared to those authored by individuals from a single nation (Glänzel & Schubert, 2001; Kwiek, 2021; Levitt & Thelwall, 2010). Other positive trends observed are that co-authored publications or higher development index of the research and innovation system of the collaborating countries receive higher citation rates compared to single-authored papers (Ronda-Pupo, 2022; Shen et al., 2020; Ullah et al., 2020). It is in this context that we want to contribute to the current literature by providing a long-term analysis of these territories.
Our objective is to explore the collaborative patterns between China, the US, and the EU in the field of computer science over a span of 31 years. We make significant contributions to the current literature in three ways. Firstly, we conduct an analysis of collaboration trends within and between these regions over time, shedding light on the dynamics of their partnerships. Additionally, because of the market-oriented possibilities of the different fields of computer science, we offer novel insights by investigating whether the institutions that participated in the article’s creation were public or private institutions. Secondly, we analyze the impact of these collaborations on the outcomes of academic and privately conducted research papers, by measuring the number of citations obtained. By evaluating the relevance and visibility of the resulting articles, we provide valuable insights into the significance of these partnerships. Lastly, we look into the prioritization of computer science subfields by the analyzed regions over time and the patterns of their shared interests. This examination allows US to uncover how the participating nations allocate their resources and focus within the realm of computer science.
In this paper, we address to answer the following research questions:
-
How much have China, the European Union, and the United States been collaborating in computer science over the years?
-
How do the collaborations between the regions affect the number of articles’ citations?
-
In which particular topics do the regions have focused on when working together?
Our research findings could be useful in assisting policymakers, lawmakers, and public agencies in making informed decisions when creating restrictions or enhancements for scientific collaboration between the analyzed regions, either in the public or private sector. These insights could inform about the historical context associated with different types of collaborations and assist in formulating effective policies that strike a balance between openness and protection of national interests. Furthermore, our findings may offer guidance to public agencies from all countries, including those analyzed in this study, for better research prioritization in the field of computer science. By analyzing the collaborative trends among the three regions, we provide valuable information about the areas of computer science that are receiving significant attention and resources, enabling the alignment of research priorities with them for potential collaborative opportunities.
The remainder of this paper is organized as follows: In “Related Work” section we discuss the related work on scientific collaborations, as well as survey current literature about the relations between China, the EU, and the US in scientific co-authorship. In “Analysis” section, we provide the details of the journal article dataset and explain the process we followed to collect and analyze it. This section then shows the results we obtained when investigating the data. Finally, we discuss the results in “Discussion” section, we draw conclusions based on the findings we got and we outline potential future research directions in “Conclusion” and “Limitations” sections , respectively.
Related work
Scientific co-authoring
Publication co-authorship has been thoroughly examined within the field of bibliometrics, which is a quantitative branch of information and library science that studies the publication of research accomplishments (Broadus, 1987). Research collaboration offers various advantages across different academic disciplines. In the fields of science, physics, and medicine, collaboration is heavily exploited, resulting in benefits such as the division of tasks and the sharing of competencies and abilities. Additionally, it plays a crucial role in improving the level of knowledge and skills of domestic scholars, fostering an environment for continued growth and development in these fields (Franceschet & Costantini, 2010; Shen et al., Limited Data Source Analysis: This study primarily relied on papers from OpenAlex for its analysis. While OpenAlex is one of the largest academic databases, it’s essential to acknowledge that different results might emerge when analyzing data from other sources. As mentioned in “Analysis” section, various data sources were examined. Still, there is potential for variations in findings when using alternative databases or sources. We recognize that our choice of data source could introduce some bias into the results, and future research might consider a more diverse set of sources to enhance the study’s robustness. In addition to this, we have only analyzed journal articles for our dataset because we consider publishing in scientific journals a general practice among the different subfields of computer science, and journal articles also represent mature and trustworthy work. This selection is also justified by its potential to facilitate future research. Comparing current results with other knowledge areas, where standard publication methods may differ (e.g., proceedings papers or posted content), opens doors for valuable insights. Geographical and Cultural Barriers: The study treated the UE27 as a single entity for simplification, which could raise concerns regarding the oversimplification of international collaborations. Existing literature has demonstrated that various barriers to collaboration, such as geographical, cultural, and political distances, can significantly impact the collaborative process (Cerdeira et al., 2023). While geographical distances might not differ significantly within Europe compared to the vast territories of China and the U.S., cultural and political distances could have a more pronounced effect on collaborations within Europe. The diversity of countries within Europe can create unique challenges in terms of international research partnerships. Neglecting the Influence of Political and Cultural Factors: Political and cultural factors play a pivotal role in international collaborations. However, this study did not focus extensively on these aspects. Future research should consider a more in-depth investigation of the influence of funding and politics on international collaborations. For instance, exploring how a country’s financial support to foreign researchers can attract talent and foster partnerships with its national research institutions is an area that could be further explored. Additionally, analyzing the impact of political factors, such as restrictive or permissive laws, on research associations can provide valuable insights into the dynamics of international collaboration. For example, restrictive laws that make obtaining visas difficult or economic incentives for international research institutions can significantly affect collaboration patterns. Heterogeneity of Collaborations within Europe: Collaborations within Europe are subject to a unique set of challenges due to the heterogeneity of the region. The study did not extensively address these disparities, which can impact collaboration dynamics. Cultural, linguistic, and political diversity within Europe can create complexities that are distinct from collaborations within more culturally and politically homogenous regions. These complexities should be acknowledged when discussing and interpreting the results. In summary, while this study has made valuable contributions to the understanding of international collaborations, it is important to recognize these limitations. Addressing the potential impact of data source selection, acknowledging the significance of geographical, cultural, and political distances, considering the influence of funding and politics, and acknowledging the heterogeneity of collaborations within Europe are essential for a comprehensive evaluation of the study’s findings. These limitations should be clearly discussed in the study’s results and limitations sections to provide a more nuanced interpretation of the research outcomes.Limitations
Notes
Although we are aware of the differences in collaboration between the European countries, we regard UE27 as a single "country" to simplify the discussions and comparisons, which is also more comparable to the USA and China in terms of economic size, population number, and the overall scientific activity than any individual country in EU.
References
Adams, J. (2013). The fourth age of research. Nature, 497(7451), 557–560.
Băzăvan, A. (2019). Chinese government’s shifting role in the national innovation system. Technological Forecasting and Social Change, 148, 119738.
Besancenot, D., Huynh, K., & Serranito, F. (2017). Co-authorship and research productivity in economics: Assessing the assortative matching hypothesis. Economic Modelling, 66, 61–80.
Biscaro, C., & Giupponi, C. (2014). Co-authorship and bibliographic coupling network effects on citations. PLoS ONE, 9(6), 99502.
Broadus, R. N. (1987). Toward a definition of bibliometrics. Scientometrics, 12, 373–379.
Burke, A., Okrent, A., Hale, K., & Gough, N. (2022) The state of US science & engineering 2022. National Science Board Science & Engineering Indicators. NSB-2022-1. National Science Foundation
Cai, X., Fry, C. V., & Wagner, C. S. (2021). International collaboration during the COVID-19 crisis: Autumn 2020 developments. Scientometrics, 126(4), 3683–3692.
Cao, C., Baas, J., Wagner, C. S., & Jonkers, K. (2020). Returning scientists and the emergence of China’s science system. Science and Public Policy, 47(2), 172–183.
Cao, C., & Suttmeier, R. P. (2017). Challenges of S &T system reform in China. Science, 355(6329), 1019–1021.
Cavero, J. M., Vela, B., & Cáceres, P. (2014). Computer science research: More production, less productivity. Scientometrics, 98, 2103–2111.
Cerdeira, J., Mesquita, J., & Vieira, E. S. (2023). International research collaboration: Is Africa different? A cross-country panel data analysis. Scientometrics, 128(4), 2145–2174.
Chinchilla-Rodríguez, Z., Sugimoto, C. R., & Larivière, V. (2019). Follow the leader: On the relationship between leadership and scholarly impact in international collaborations. PLoS ONE, 14(6), 0218309.
Dan, M.-C. (2013). Why should university and business cooperate? A discussion of advantages and disadvantages. International Journal of Economic Practices and Theories, 3(1), 67–74.
Färber, M. (2019). The microsoft academic knowledge graph: A linked data source with 8 billion triples of scholarly data. In The Semantic Web–ISWC 2019: 18th International Semantic Web Conference, Auckland, New Zealand, October 26–30, 2019, Proceedings, Part II 18 (pp. 113–129). Springer
Fernandes, J. M., & Monteiro, M. P. (2017). Evolution in the number of authors of computer science publications. Scientometrics, 110(2), 529–539.
Fiala, D., & Tutoky, G. (2017). Computer science papers in web of science: A bibliometric analysis. Publications, 5(4), 23.
Franceschet, M. (2011). Collaboration in computer science: A network science approach. Journal of the American Society for Information Science and Technology, 62(10), 1992–2012.
Franceschet, M., & Costantini, A. (2010). The effect of scholar collaboration on impact and quality of academic papers. Journal of Informetrics, 4(4), 540–553.
Glänzel, W., & Schubert, A. (2001). Double effort= double impact? A critical view at international co-authorship in chemistry. Scientometrics, 50(2), 199–214.
Harhoff, D., Mueller, E., & Van Reenen, J. (2014). What are the channels for technology sourcing? Panel data evidence from German companies. Journal of Economics & Management Strategy, 23(1), 204–224.
Krige, J. (2008). American hegemony and the postwar reconstruction of science in Europe. MIT Press.
Kwiek, M. (2021). The globalization of science: The increasing power of individual scientists. Nauka, 4, 37–66.
Lacey, S. (2021) Technological decoupling: Can US lose the pre-eminence race to China? Trends Research & Advisory
Lancho-Barrantes, B. S., Guerrero-Bote, V. P., & Moya-Anegón, F. (2010). What lies behind the averages and significance of citation indicators in different disciplines? Journal of Information Science, 36(3), 371–382.
Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Bibliometrics: Global gender disparities in science. Nature, 504(7479), 211–213.
Lee, J. J., & Haupt, J. P. (2020). Winners and losers in US-China scientific research collaborations. Higher Education, 80, 57–74.
Levitt, J., & Thelwall, M. (2010). Does the higher citation of collaborative research differ from region to region? A case study of economics. Scientometrics, 85(1), 171–183.
Lewis, M. (2021) Time to end the US Justice Department’s China initiative. Foreign Affairs Newsletter, July 22, 2021
Leydesdorff, L., Wagner, C. S., & Bornmann, L. (2014). The European Union, China, and the United States in the top-1 and top-10 layers of most-frequently cited publications: Competition and collaborations. Journal of Informetrics, 8(3), 606–617.
Li, A. C., & Chang, C. C. (2014) Beyond competition: Past, present and future on EU-China science and technology collaboration. European Foreign Affairs Review,19(Special)
Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences,101(suppl-1), 5200–5205.
Priem, J., Piwowar, H., & Orr, R. (2022) Openalex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. ar**v:2205.01833
Puuska, H.-M., Muhonen, R., & Leino, Y. (2014). International and domestic co-publishing and their citation impact in different disciplines. Scientometrics, 98, 823–839.
Ronda-Pupo, G. A. (2022) Is the immediacy index of co-authored papers higher than that of single-authored ones? Transinformação, 34
Schmidt, K. (2017) Patterns of economic thought in German-American research cooperation after world war ii—The “rencontres de st-gall” and other cases. German Influences on American Economic Thought and American Influences on German Economic Thought: Deutsche Einflüsse auf amerikanisches wirtschaftswissenschaftliches Denken und amerikanische Einflüsse auf deutsches Wirtschaftsdenken. Studien zur Entwicklung der ökonomischen Theorie XXXII, 299
Schüller, M., & Schüler-Zhou, Y. (2020). United States–China Decoupling: Time for European Tech Sovereignty. GIGA Focus Asia, 7. Hamburg: German Institute for Global and Area Studies (GIGA). https://nbn-resolving.org/urn:nbn:de:0168-ssoar-71026-4
Shen, H., **e, J., Li, J., & Cheng, Y. (2021). The correlation between scientific collaboration and citation count at the paper level: A meta-analysis. Scientometrics, 126(4), 3443–3470.
Silver, A., Noorden, R., & Subbaraman, N. (2020). US crackdown harms Chinese collaborations. Nature, 583(7816), 341–342.
Suttmeier, R. P. (1997). Emerging innovation networks and changing strategies for industrial technology in China: Some observations. Technology in Society, 19(3–4), 305–323.
Tang, L., & Shapira, P. (2011). China-US scientific collaboration in nanotechnology: Patterns and dynamics. Scientometrics, 88(1), 1–16.
Ullah, A., Aria, A., & Akhter, M. N. (2020). EU trade policy amid US-China trade confrontation. Journal of Social and Political Sciences,3(1)
Vieira, E. S. (2023). The influence of research collaboration on citation impact: The countries in the European innovation scoreboard. Scientometrics, 1–25.
Wagner, C. S., Bornmann, L., & Leydesdorff, L. (2015). Recent developments in China-US cooperation in science. Minerva, 53, 199–214.
Wagner, C.S., & Cai, X. (2022) Changes in co-publication patterns among China, the European Union (28) and the United States of America, 2016-2021. ar**v:2202.00453
Wagner, C. S., & Cai, X. (2022). Drop in China-USA international collaboration. News,15(2)
Wagner, C. S., Park, H. W., & Leydesdorff, L. (2015). The continuing growth of global cooperation networks in research: A conundrum for national governments. PLoS ONE, 10(7), 0131816.
Wagner, C. S., Whetsell, T. A., & Leydesdorff, L. (2017). Growth of international collaboration in science: Revisiting six specialties. Scientometrics, 110, 1633–1652.
Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365–391.
Wang, L., Wang, X., & Philipsen, N. J. (2017). Network structure of scientific collaborations between China and the EU member states. Scientometrics, 113, 765–781.
White, K. (2019) Publications output: US trends and international comparisons. Science & Engineering Indicators 2020. NSB-2020-6. National Science Foundation
**wei, Z., & **angdong, Y. (2007). Science and technology policy reform and its impact on China’s national innovation system. Technology in Society, 29(3), 317–325.
Yuan, L., Hao, Y., Li, M., Bao, C., Li, J., & Wu, D. (2018). Who are the international research collaboration partners for China? A novel data perspective based on NSFC grants. Scientometrics, 116, 401–422.
Zhang, Z., Rollins, J. E., & Lipitakis, E. (2018). China’s emerging centrality in the contemporary international scientific collaboration network. Scientometrics, 116(2), 1075–1091.
Zhao, B., Gu, Y., Forde, J.Z., & Saphra, N. (2022) One venue, two conferences: The separation of Chinese and American citation networks. ar**v:2211.12424
Zhao, L., & Yin, X. (2019). Technology as a battleground: US demands, China’s responses. East Asian Policy, 11(02), 24–33.
Funding
Open access funding provided by University of Innsbruck and Medical University of Innsbruck. The authors did not receive support from any organization for the submitted work.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no competing interests to declare that are relevant to the content of this article.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Gómez-Espés, A., Färber, M. & Jatowt, A. Benefits of international collaboration in computer science: a case study of China, the European Union, and the United States. Scientometrics 129, 1155–1171 (2024). https://doi.org/10.1007/s11192-023-04902-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-023-04902-3