Analysis Of Research Trends Related To Children's Picture Books Using Text Mining

Abstract

This study aims to examine research trends in the field of children picture books by analyzing academic papers published as keywords of 'child picture books' from 2000 to 2021. The research target papers were 1,216 domestic academic papers collected using the database of academic research information services, and analyzed using a network analysis method using big data. First, as a result of examining the frequency analysis and connection centrality of major keywords in research papers from 2000 to 2021, studies related to picture books, children, and languages were mainly focused. Second, as a result of analyzing the network visualization of research related to children picture books, papers on picture books, languages, and children were mainly conducted in Wordcloud, but studies related to literature, creativity, activities, and education were also found to be high. Third, as a result of analysis with the N-gram network, studies on literature, emotion, and language showed connectivity. As a result of analysis with the CONCOR network, it was classified into eight groups, and picture books and children were calculated as the highest ranking in topic modeling. This study is meaningful in exploring future research topics and directions related to children picture books and providing necessary basic data as it can objectively grasp the relevance between topics and trends of the times in research related to children picture books.