빅데이터 분석을 이용한 코로나 19 이후 경호 관련 학과의 사회적 인식 분석

Abstract

Objectives The purpose of this study is to analyze society's overall perception of universities' security-related departments through big data, provide basic data for the development of security-related departme.
 Methods Under the keyword “University + Security,” data from major domestic portal sites were collected and refined from January 20, 2020 to March 31, 2023, when the first COVID-19 confirmed case in Korea was found, and word cloud analysis, network analysis and centrality analysis, and CONCOR analysis were conducted.
 Results First, through word cloud analysis of the top 30 keywords of frequency, ‘police’ was found to be an overwhelmingly frequent keyword. Second, in network analysis, “police” was confirmed to be the most important keyword, and words such as “police”, “security”, “administration”, “major”, and “sports” showed high connectivity in connection centrality analysis. In the mediation centrality analysis, it was confirmed that most keywords serve as bridges between nodes and are actively connected. Third, in the CONCOR analysis, it was confirmed that it was clustered into six groups, and the cluster name was determined as ‘public security and After Graduation’, ‘Curriculum and Employment’, ‘University Promotion’, ‘physical education’, ‘Daegu’, and ‘Other’.
 Conclusions It was confirmed that the police and security have a close relationship in people's perceptions, and it is believed that it would be a desirable direction to properly utilize them and reflect them in security-related departments. IIt is necessary to develop and apply a curriculum that can strengthen the systematicity of education and enhance expertise to induce students' interest. It is necessary to use it as an advantage of security-related departments by increasing positive awareness and interest in bodyguards, and it will be helpful to prepare and present specific plans for students' careers and post-graduation plans, and to find and advance to public security.