Topic modelling-based analysis of COVID-19 vaccine articles published in the preprint server MedRxiv

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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.

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Deshpande, N., Ligade, V., Shaikh, S. A., & Khode, A. (2023). Topic modelling-based analysis of COVID-19 vaccine articles published in the preprint server MedRxiv. Annals of Library and Information Studies, 70(1), 41–51. https://doi.org/10.56042/alis.v70i1.71939

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