Computer Science Research and COVID-19: A Review of Bibliometric Visualization and Proposed Method - Rachael Rickta, Patrick; Syahrul Nizam, Junaini (2021)
The pandemic of COVID-19 has accelerated significantly, generating great concern throughout the world. As a result, the quantity of articles and journals published on COVID-19 has increase rapidly. However, these publications do not cover bibliometric visualisation sufficiently, particularly in the computer science field. Thus, the purpose of this article is to conduct a review of the literature on bibliographic visualisation. We analysed four websites that present COVID-19 bibliographic data. Additionally, we propose a framework for visually representing bibliometric data pertaining to computer science research and COVID-19. We believe that our method for bibliometric visualisation will considerably benefit future research by serving as a guide. It will serve as a significant way for conduction COVID-19 bibliometric visualization, in other areas, not limited to the field of computer science.