A Big Data to Discovery: Network Analysis of COPD Research Collaborations from 2000 to 2023

Introduction: Collaborative research is critical for advancing knowledge of chronic obstructive pulmonary disease (COPD). Over the last two decades, understanding the structure and evolution of research networks can provide insights into key contributors and trends in international cooperation. This study aimed to analyze the structure and evolution of collaborative networks in COPD research from 2000 to 2023, identifying key researchers and trends in international cooperation using co-authorship network analysis.

Methods:  A dataset of 74,024 COPD-related publications indexed in the Web of Science (WoS) Core Collection was analyzed using Python (Version 3.10.5) in PyCharm (Version 2022.1.3). Macro-level metrics (network density, clustering coefficient, components, average path length) and micro-level metrics (degree centrality, closeness centrality, betweenness centrality) were calculated to evaluate collaboration intensity and researcher roles.

Results: The analysis revealed progressive growth in network density (from 0.00023 in 2000-2009 to 0.00020 in 2020-2023) and clustering coefficient (from 0.885 to 0.893), reflecting strengthened collaboration. Notable researchers, including P.J. Barnes (2000-2009), E.K. Silverman (2010-2019), and R.G. Barr (2020-2023), were identified as central figures. Despite improvements, network fragmentation remains a challenge. Many isolated components exist, and average distances between research groups remain infinite across all periods.

Conclusion: Chronic obstructive pulmonary disease research collaboration has grown significantly over the past two decades, driven by key contributors and increasingly cohesive local networks. However, the persistent fragmentation of the global network highlights the need for further integration to enhance knowledge dissemination and innovation. These findings underscore the importance of fostering broader, more inclusive international collaborations.