Title:	DETERMINATION OF RESEARCH TRENDS IN COVID-19 LITERATURE USING TOPIC MODEL APPROACH
Author(s):	Eda Sonmez and Keziban Seckin Codal
ISBN:	978-989-8704-27-6
Editors:	Miguel Baptista Nunes, Pedro Isaías and Philip Powell
Year:	2021
Edition:	Single
Keywords:	COVID-19, Topic Modeling, LDA, Research Trends, Information Systems
Type:	Full
First Page:	161
Last Page:	169
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	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.
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