Topic modelling-based analysis of COVID-19 vaccine articles published in the preprint server MedRxiv
Document Type
Article
Publication Title
Annals of Library and Information Studies
Abstract
Two thousand one hundred and ninety-eight research publications on COVID-19 vaccines in MedRxiv preprint repository during January 01, 2020 and December 31, 2021 were analyzed for topic modelling with unsupervised inference method. Latent Dirichlet Allocation (LDA) method was used to investigate the thematic structure of the preprints. It was observed that the published articles were related to either clinical trials or patient responses to vaccine or modelling for various applications such as infection transmission, vaccine allocation, vaccine hesitancy etc.
First Page
41
Last Page
51
DOI
10.56042/alis.v70i1.71939
Publication Date
1-1-2023
Recommended Citation
Deshpande, Nishad; Ligade, Virendra; Shaikh, Shabib Ahmed; and Khode, Alok, "Topic modelling-based analysis of COVID-19 vaccine articles published in the preprint server MedRxiv" (2023). Open Access archive. 9116.
https://impressions.manipal.edu/open-access-archive/9116