Research Method of Clustering of COVID-19 with Text-mining

Abstract

A suspected patient with symptoms similar to coronavirus infection-19 was identified for the first time on January 8, 2020 in Korea. After that, the world was dominated by COVID-19. People all around the world must face a new society that will be changed by COVID-19. To prepare for such future, this study collected related words around the keyword COVID-19 and has predicted what risk factors and opportunity factors occur. As a result of SNA analysis by collecting news data from January to May, 2020, when COVID-19 was rapidly spreading, the key words “Prevention of epidemics”, “Inspection”, “Quarantine”, “Infection”, “Government”, Keywords such as “Patient”, “Addition”, “Diffusion”, “Judgment” and “Prohibition” have had important influences. Furthermore, COVID-19 has been affecting the daily lives of individual citizens, and their interest in the government response process increased. Therefore, the response to the new infectious disease must be quarantine based on science and technology and data, and it is imperative to establish a legal basis for using social facilities as treatment facilities.