The new science of COVID-19: A Bibliographic and Network Analysis

• Main Author: Fan, Xuezhou
• Format: Journal Article
• Language: English
• Published: 17-07-2024
• Subjects: Computer Science - Digital Libraries; Computer Science - Social and Information Networks
• DOI: 10.48550/arxiv.2407.15867

Since the outbreak of the COVID-19, there have been many scientific
publications studying the COVID-19. The purpose of this study is to identify
the research trend, collaboration pattern, most influential elements, etc. from
scientific publications related to COVID-19 in 2020, by using bibliographic
analysis and network analysis. In Chapter 1 and Chapter 2, motivation behind
this paper is introduced. Some previous similar studies are discussed.
Comparisons are made in different aspects, such as data collection methods,
data analysis tools and methods, etc. Their advantages and limitations compared
to this paper are also addressed. In Chapter 3, important concepts used in this
paper related to bibliographic analysis such as h-index and g-index, and
network analysis such as centrality measures and assortativity are introduced.
Networks with small-world property and scale-free property will also be
studied. In Chapter 4 and Chapter 5, the way the data are obtained for the
analysis of this paper is introduced step by step. Full result is shown. In
Chapter 6, conclusions are arrived. A general growing trend of the number of
the publications is observed, due to the efforts made by scientific
researchers. Meanwhile, measures should also be taken to encourage future study
in this field.