Developing a novel algorithm for comparing cluster patterns in networks on journal articles during and after COVID-19: Bibliometric analysis.

Published in: Medicine (2024)

This research effectively created and utilized CPCA to analyze cluster patterns in bibliometrics. It underscores notable identical patterns in country-/department-/keyword based clusters, but dissimilar and different in institute-/author- based clusters, between these 2 stages during and after COVID-19, offering a framework for future bibliographic studies to compare cluster patterns beyond just the CIDA entities, as demonstrated in this study.

Keyphrases

coronavirus disease
sars cov
machine learning
deep learning
respiratory syndrome coronavirus
neural network