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Keisuke Okamura
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Journal Articles
Publisher: Journals Gateway
Quantitative Science Studies (2023) 4 (4): 938–959.
Published: 01 November 2023
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Recent decades have witnessed a dramatic shift in the cross-border collaboration mode of researchers, with countries increasingly cooperating and competing with one another. It is crucial for leaders in academia and policy to understand the full extent of international research collaboration, their country’s position within it, and its evolution over time. However, evidence for such world-scale dynamism is still scarce. This paper provides unique evidence of how international collaboration clusters have formed and evolved over the past 50 years across various scientific publications, using data from OpenAlex, a large-scale open bibliometrics platform launched in 2022. I first examine how the global presence of top-tier countries has changed in 15 natural science disciplines over time, as measured by publication volumes and international collaboration rates. Notably, I observe that the United States and China have been rapidly moving closer together for decades but began moving apart after 2019. I then perform a hierarchical clustering to analyze and visualize the international collaboration clusters for each discipline and period. Finally, I provide quantitative evidence of a “Shrinking World” of research collaboration at a global scale over the past half-century. My results provide valuable insights into the big picture of past, present, and future international collaboration.
Includes: Supplementary data
Journal Articles
Publisher: Journals Gateway
Quantitative Science Studies (2022) 3 (1): 122–146.
Published: 12 April 2022
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Scholarly communications have been rapidly integrated into digitized and networked open ecosystems, where preprint servers have played a pivotal role in accelerating the knowledge transfer processes. However, quantitative evidence is scarce regarding how this paradigm shift beyond the traditional journal publication system has affected the dynamics of collective attention on science. To address this issue, we investigate the citation data of more than 1.5 million eprints on arXiv ( https://arxiv.org ) and analyze the long-term citation trend for each discipline involved. We find that the typical growth and obsolescence patterns vary across disciplines, reflecting different publication and communication practices. The results provide unique evidence of the attention dynamics shaped by the research community today, including the dramatic growth and fast obsolescence of Computer Science eprints, which has not been captured in previous studies relying on the citation data of journal papers. Subsequently, we develop a quantitatively and temporally normalized citation index with an approximately normal distribution, which is useful for comparing citational attention across disciplines and time periods. Further, we derive a stochastic model consistent with the observed quantitative and temporal characteristics of citation growth and obsolescence. The findings and the developed framework open a new avenue for understanding the nature of citation dynamics.
Includes: Supplementary data