Visual Analysis of the National Characteristics of the COVID-19 Vaccine Based on Knowledge Graph

Abstract

The aim is to construct a country-dimension knowledge graph of COVID-19 vaccines from the information of COVID-19 vaccines and to analyze the leading countries of vaccine R&D by combining the advantages of easy operation and intuitive feeling of knowledge graph visualization, to provide a reference for Chinese vaccine R&D departments and international cooperation. In this paper, through data collection, based on entity extraction and relationship construction, a knowledge graph of country dimensions was established by specifying the central vaccine R&D countries and vaccine distribution, and multidimensional microdata such as word frequency and betweenness centrality were combined to analyze the national characteristics of the COVID-19 vaccine. The analysis of the knowledge graph of the country dimension of the COVID-19 vaccine shows that countries with robust technology and economies, such as the US and China, choose to develop vaccine distribution independently, countries with advanced economies, such as Saudi Arabia, decide to purchase vaccine distribution, and less developed countries, such as South Africa and Latin America, need international aid for vaccines or purchase low-cost vaccines. This paper constructs the correlation between nodes and nodes of the COVID-19 vaccine with the help of a knowledge graph, systematically and comprehensively reveals the research mainstay and distribution model of the COVID-19 vaccine from the national level, and provides rationalized suggestions for international cooperation in vaccine R&D in China.