paper 2021 ยท Procedia Computer Science

Analysis of Patterns and Trends in COVID-19 Research

C. Dornick, A. Kumar, S. Seidenberger, E. Seidle, P. Mukherjee

DOI

Abstract

This paper applies natural language processing and bibliometric analysis to the rapidly growing body of COVID-19 research. We identify dominant topics, collaboration patterns, and temporal trends across the pandemic literature.

Key Results

  • Identified major research clusters and topic evolution over time
  • Collaboration networks show increasing international cooperation
  • NLP-based topic modeling reveals underexplored research areas