소셜 빅 데이터 분석을 통한 지방대학의 위기 분석과 그 극복 방안 (Analysis and Overcoming Measures of Crisis in Local Universities through Social Big Data Analysis)

서지정보

· 발행기관 : 한국비교정부학회
· 수록지 정보 : 한국비교정부학보 / 25권 / 2호 / 215 ~ 252페이지
· 저자명 : 이상엽

초록

(Purpose) Recently, universities have called for a comprehensive and strategic overhaul of human resource development due to changes in the number of school-age population, entering an aging society, diversity in education demand due to population diversification, popularization of higher education, and non-face-to-face learning due to Covid-19. In particular, special measures are needed as the crisis at local universities is accelerating due to the disappearance of local areas and a sharp drop in the number of admissions population. To establish an effective and responsive university support policy, social changes and opinions which cannot be identified by simple questionnaire survey and interviews with the participants should be reflected through the social big data in which various social perceptions and participants’ opinions are explicitly and implicitly reflected. In this paper, I analyzed how university members and the general public are changing their perceptions of the crisis of local universities due to the decrease in local population over the past five years through social big data analysis.
(Design/methodology/approach) Data collection period is a total of 5 years from April 1st 2016 to March 31st 2021, and the data were collected yearly basis. Collection channels are blogs (Naver, Daum) and Facebook. Keywords were crisis of local universities, lack of recruitment, closure of universities, abolition of departments, enrollment quota, recruitment rate of freshmen, shortage of enrollment rate, etc.. Textom and UCINET6 / Netdraw were used as analysis tools. Regarding analysis techniques, keywords were identified through the analysis of occurrence frequency of yearly collected data, and yearly centrality (connection centrality, eigenvetor centrality) were analyzed. Based on yearly keywords, semantic network analysis was subsequently conducted. Total number of collected data was 97,491, (Findings) According to an analysis of the annual topic terms, keywords such as "university", "enrollment recruitment", "not filled", "enrollment quota", "local university", "recruitment of students" and "new students" appeared frequently.
As a result of checking the centrality value, keywords such as "university", "enrollment recruitment", "not filled", "enrollment quota", Other influential keywords included "grade", "local university", "new students", "recruitment", "admission", "student" and "local". The keyword's meaning network showed a high degree of connection between "university-local", "university-capital university", "university-local university", "university-enrollment recruitment", and "university-filling" (Research implications or Originality) In the policy alternative section, the government's policies related to the adjustment of the admission quota of universities, measures at the local university level, departmental efforts, and measures to attract students to local and local universities were proposed.

영어초록

(Purpose) Recently, universities have called for a comprehensive and strategic overhaul of human resource development due to changes in the number of school-age population, entering an aging society, diversity in education demand due to population diversification, popularization of higher education, and non-face-to-face learning due to Covid-19. In particular, special measures are needed as the crisis at local universities is accelerating due to the disappearance of local areas and a sharp drop in the number of admissions population. To establish an effective and responsive university support policy, social changes and opinions which cannot be identified by simple questionnaire survey and interviews with the participants should be reflected through the social big data in which various social perceptions and participants’ opinions are explicitly and implicitly reflected. In this paper, I analyzed how university members and the general public are changing their perceptions of the crisis of local universities due to the decrease in local population over the past five years through social big data analysis.
(Design/methodology/approach) Data collection period is a total of 5 years from April 1st 2016 to March 31st 2021, and the data were collected yearly basis. Collection channels are blogs (Naver, Daum) and Facebook. Keywords were crisis of local universities, lack of recruitment, closure of universities, abolition of departments, enrollment quota, recruitment rate of freshmen, shortage of enrollment rate, etc.. Textom and UCINET6 / Netdraw were used as analysis tools. Regarding analysis techniques, keywords were identified through the analysis of occurrence frequency of yearly collected data, and yearly centrality (connection centrality, eigenvetor centrality) were analyzed. Based on yearly keywords, semantic network analysis was subsequently conducted. Total number of collected data was 97,491, (Findings) According to an analysis of the annual topic terms, keywords such as "university", "enrollment recruitment", "not filled", "enrollment quota", "local university", "recruitment of students" and "new students" appeared frequently.
As a result of checking the centrality value, keywords such as "university", "enrollment recruitment", "not filled", "enrollment quota", Other influential keywords included "grade", "local university", "new students", "recruitment", "admission", "student" and "local". The keyword's meaning network showed a high degree of connection between "university-local", "university-capital university", "university-local university", "university-enrollment recruitment", and "university-filling" (Research implications or Originality) In the policy alternative section, the government's policies related to the adjustment of the admission quota of universities, measures at the local university level, departmental efforts, and measures to attract students to local and local universities were proposed.

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