This research aims to apply the method of semantic network analysis to analyze and take a look at research trends of music education by identifying the correlations between relevant subjects. Further, it seeks to explore the possibility of applications of semantic network analysis in other research fields of music education as well as research trends. The subject materials for analysis are abstracts of 171 theses on ‘Korean Journal of Research in Music Education’ published by the Korean Music Education Society, one of the leading academic publishers on music education in South Korea, over five years from 2010 to 2014. Analysis was conducted on the number of connecting links, the centrality of the connecting degree, and the centrality of mediums by analyzing the contents with KrKwic, a program to analyze Korean messages and visualizing them with NetDraw of UCINET, a semantic network analysis program. The results of analysis showed that among major terms consisting of music education research are ‘music’, ‘education’, ‘teacher’, ‘class’, ‘tutoring’, and so on, and ‘music’ has a closer relevance with music in school. It was also notable that music education research is more closely connected to ‘teachers’ rather than ‘students’. This research has implications in that it explored the possibility of application of the research in various fields of music education research as well as being useful to supplement the methodologies of analyzing the trends of current music education research.