Analysis of Research Trends in Regional Innovation Using Text Mining

Abstract

To aid local governments in solving various regional innovation issues related to regional development, trend analyses should first be conducted. In this study, 579 abstracts published in academic journals between year 2003 and year 2015 were analyzed to examine the research trends of topics related to regional innovation through a keyword frequency analysis and a social network analysis, both of which are text mining techniques. As a result of these analyses, the most frequent keyword that appeared through the clustering of participating entities was regional innovation system during the Roh Moo-Hyun administration. During the Lee Myung-Bak administration, the most frequent keyword obtained through the participation of local residents was regional innovation focused on overall business development, which continued through to the Park Geun-Hye administration. This study suggests a big data analysis method to derive the core problems related to regional innovation and may trigger follow-up research. Furthermore, the results of this study can be used as basic data for local governments and administrative agencies to establish regional innovation policies.