Preprint Article Version 1 This version is not peer-reviewed

SGLT2 Research Collaboration Networks: Structural and Temporal Dynamics in Scientific Cooperation

Version 1 : Received: 7 October 2024 / Approved: 7 October 2024 / Online: 8 October 2024 (03:11:21 CEST)

How to cite: Ogasawara, N. SGLT2 Research Collaboration Networks: Structural and Temporal Dynamics in Scientific Cooperation. Preprints 2024, 2024100495. https://doi.org/10.20944/preprints202410.0495.v1 Ogasawara, N. SGLT2 Research Collaboration Networks: Structural and Temporal Dynamics in Scientific Cooperation. Preprints 2024, 2024100495. https://doi.org/10.20944/preprints202410.0495.v1

Abstract

Aim: This study aims to explore the collaborative networks in Sodium/Glucose Cotransporter 2 (SGLT2) research, covering the period from 2000 to 2023. By conducting a co-authorship network analysis, I investigate the structure and dynamics of scientific collaboration, identifying key researchers, institutions, and trends in the field. This analysis provides insights into how research collaboration has evolved and highlights the influence of international cooperation on the development of SGLT2 research.Method: The data were collected from the Web of Science (WoS) Core Collection and included 6,999 publications on SGLT2 research. Using Python (Version 3.10.5) in the PyCharm development environment (Software Version 2022.1.3), I analyzed both macro and micro-level network indicators. Macro-level indicators included network density, clustering coefficient, components, and average distance, while micro-level indicators included degree centrality, closeness centrality, and betweenness centrality. These metrics were used to assess the structure of the co-authorship network and identify key contributors.Result: The network analysis revealed significant changes in collaboration patterns over the study period. From 2000 to 2023, the network became more fragmented, with an increase in the number of research clusters and components. However, influential researchers, such as Zinman B. and Heerspink Hiddo J. L., consistently emerged as central figures in terms of both degree and closeness centrality. The analysis also highlighted the rise of international collaboration, particularly involving researchers from the United States, Europe, and Asia, with Japan playing a growing role in recent years.Conclusion: This study demonstrates that SGLT2 research collaboration networks have evolved considerably over the last two decades. The identification of key researchers and institutions provides valuable insights into the field's development, emphasizing the importance of international cooperation in advancing SGLT2 research. These findings may guide future research strategies and promote further collaborative efforts.

Keywords

Endocrinology and Metabolism; SGLT2; co-authorship network analysis; network analysis; research collaboration; research trend analysis; research trends; key researchers; research strategies; internal medicine; planning future collaborative studies; interdisciplinary approach

Subject

Medicine and Pharmacology, Endocrinology and Metabolism

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