Analysis of Scientific Publications During the Early Phase of the COVID-19 Pandemic: Topic Modeling Study.

ABSTRACT:

Background

The COVID-19 pandemic has spread at an alarming speed, and effective treatment for the disease is still lacking. The body of evidence on COVID-19 has been increasing at an impressive pace, creating the need for a method to rapidly assess the current knowledge and identify key information. Gold standard methods such as systematic reviews and meta-analyses are regarded unsuitable because they have a narrow scope and are very time consuming.

Objective

This study aimed to explore the published scientific literature on COVID-19 and map the research evolution during the early phase of the COVID-19 pandemic.

Methods

We performed a PubMed search to analyze the titles, keywords, and abstracts of published papers on COVID-19. We used latent Dirichlet allocation model

SUBMITTER: Alga A 

PROVIDER: S-EPMC7674137 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature