A bibliometric analysis of COVID-19 research in Malaysia using Latent Dirichlet Allocation - Zamira Hasanah Zamzuri (Penerbit Universiti Kebangsaan Malaysia, 2021)
Coronavirus COVID-19 shocking the whole world due to its highly contagious characteristics implicating not only public health, but also economy and social life. Since the effects are momentous, plenty of research have been conducted and still ongoing in order to study and to learn more about this virus and how it changing our daily life. In this paper, we explore 134 articles published in 2020 related to COVID-19 and narrowing the scope of study to Malaysia. An alternative route was taken by employing Latent Dirichlet Allocation (LDA) to identify underlying themes or topics in these publications. Two separate analyses were conducted, one is to the paper’s titles and another one to the journal’s names. The findings identified three topics for paper’s titles data are clinical study, impact of COVID-19 on various fields and Movement Control Order (MCO). The last topic shows the locality criterion in the studied papers as the term MCO was only used in Malaysia. For the journal’s names, three topics identified were medical study, public health also business and education. Two papers with the most number of citations are both in social sciences. Investigating the properties of these topics, we found that papers on clinical studies are the ones with more chance to be cited and published by reputable publishers. These findings may help researchers on planning and strategizing for future research on COVID-19 specifying on Malaysia cases.