Research Trends Analysis in Educational Journal Publications on Covid19 Using Descriptive and Text Mining Methods :Preliminary Analysis

Abstract

The study aims to reveal the studies' profile on covid19 in journals in the field of education. For this purpose, probabilistic topic modeling technique and decriptive analysis has been used to together to analyze 3039 journal articles that are indexed by the SCOPUS database between January 2020 and May 2021. Within the scope of decriptive analysis, the most cited journals, the most publishing journals, and the most publishing countries were analyzed. In probabilistic topic modeling stage, Latent Dirichlet allocation (LDA) algorithm which is a text mining method was applied to the abstracts of those extracted documents to identify topics in publications containing keywords such as covid, corona, pandemic in their titles. The results of text mining revealed 10 major topics mapping the the studies' profile on covid19 in journals in the field of education. In this study, preliminary analysis results were given.