Online Information Sources of Coronavirus Using Webometric Big Data

코로나19 사태와 온라인 정보의 다양성 연구 - 빅데이터를 활용한 글로벌 접근법

  • Park, Han Woo (Interdisciplinary Graduate Programs of Digital Convergence Business and East Asian Cultural Studies, Department of Media and Communication, YeungNam University) ;
  • Kim, Ji-Eun (Cyber Emotions Research Institute, YeungNam University) ;
  • Zhu, Yu-Peng (Cyber Emotions Research Institute, YeungNam University)
  • 박한우 (영남대학교 언론정보학과, 디지털융합비즈니스학 및 동아시아문화학 협동과정 대학원) ;
  • 김지은 (영남대학교 디지털융합비지니스학 대학원, 사이버감성연구소) ;
  • 주우붕 (영남대학교 디지털융합비지니스학 대학원, 사이버감성연구소)
  • Received : 2020.07.13
  • Accepted : 2020.11.06
  • Published : 2020.11.30


Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.