Analysing Scientific Collaboration Networks Using Network Science Techniques to Study Covid-19 preprint papers/articles in UK and USA

Abstract

The COVID-19 pandemic has instigated an unparalleled surge in scientific research, necessitating extensive collaboration among researchers, institutions, and nations. In this study, we employ advanced network science techniques, including centrality and betweenness measures, to conduct a comprehensive analysis of scientific collaboration networks within the context of COVID-19 research. The focus is specifically on preprint papers and articles sourced from Kaggle databases in the UK and USA. The research methodology involves collecting and analyzing over 50 million preprint papers and articles to provide a robust foundation for the analysis. Building upon existing research, we utilize bibliometric analyses and network science methodologies to unveil the intricate dynamics of collaboration. By mapping and quantifying evolving collaboration patterns, this research aims to identify key players and uncover research hotspots. The inclusion of network science methods such as centrality and betweenness enriches the analysis, providing a nuanced understanding of the collaborative landscape. The findings not only present a comprehensive view of collaborative dynamics within the scientific community but also shed light on key network metrics, including centrality and betweenness, highlighting pivotal contributors and facilitating efficient information flow. The paper contributes to the ongoing discourse on global health crises, offering valuable insights into the collaborative responses to the pandemic. The study, encompassing 32 papers over the period 2020 to 2023, represents a significant and timely addition to the existing body of knowledge. As the global scientific community continues to grapple with the complexities of COVID-19, this research serves as an essential guide for informed decision-making by policymakers, researchers, and institutions involved in shaping strategies for both current and future pandemics. The incorporation of new results further enhances the relevance and applicability of the findings, positioning this study as a crucial contribution to the understanding of collaborative networks in the face of global health challenges.