Determination of research trends in COVID-19 literature using topic model approach

Sonmez E., Codal K. S.

14th IADIS International Conference Information Systems 2021, Virtual, Online, 3 - 05 March 2021, pp.161-169 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Virtual, Online
  • Page Numbers: pp.161-169
  • Keywords: COVID-19, Information Systems, LDA, Research Trends, Topic Modeling
  • Ankara Yıldırım Beyazıt University Affiliated: Yes


© 14th IADIS International Conf. Infor. Sys. 2021. All rights reserved.The world is currently facing a significant global health crisis that threatens millions of lives. Researchers and scholars have united to create a network and knowledge maps for the novel crisis of coronavirus (COVID-19) pandemic. During a pandemic, identifying the fields of scientific study that have attracted greater research attention with the pandemic is of paramount importance in managing the pandemic. This paper aims to identify a number of popular subjects of research related to COVID-19 through topic modeling, as well as to demonstrate the role of information systems (IS) to raise awareness of new research. In this context, a corpus of 7,395 English articles related to COVID-19 published in the Web of Science database was analyzed by using the Latent Dirichlet Allocation (LDA) and the topics were identified, which are classified into five main themes: epidemiological studies, clinical studies, global impacts of COVID-19, guidelines regarding the challenges of COVID-19, and the role of information systems to manage the COVID-19 outbreak. The findings suggest that epidemiological and clinical studies are the core research topics in this respect, in line with the findings of a number of previous studies, while global impacts of COVID-19, guidelines regarding the challenges of COVID-19, and use of information systems in COVID-19 pandemic are new trend topics of COVID-19 research.