Analysis of Text Mining Keyword Issues for Defense Drone on Social Network

Abstract

Research on weapon systems has been conducted, and defense drones have been developed. However, few analyses that identify the needs of the general public have been conducted. The purpose of this study is to analyze the issues of interest in social networks regarding defense drones and extract keywords for activation. In this study, big data analysis tools such as Textom, Ucinet6, and NetDraw were used. The results of the keyword frequency analysis, centrality analysis, and CONCOR analysis showed that public information regarding social networks expressed keywords in defense drones, such as Defense Daily, News, Enterprise, Defense Science Research Institute, University, Hydrogen Battery, Army, Air Force, Urban Transportation, Fire, Regional, Enterprise, and Research. It is necessary to revitalize media publicity in developing cooperative technologies by companies, universities, the National Defense Research Institute, urban transportation, and firefighting, using army and air force drones, and developing future hydrogen batteries. In addition, issues of interest were observed for contents, such as applications in the United States, Israel, North Korea, Iran, and Afghanistan, and fostering university education. There is a need to present a case for the actual military use of defense drones and train the department of defense drones at universities.