기후변화 대응 유관 지표 내 키워드 중복도 및 유사성 분석: 키워드 기반 상향식 접근 (Multiplicity and similarity analysis of climate change-related indicators: A keyword-based bottom-up approach)

서지정보

· 발행기관 : 한국기후변화학회
· 수록지 정보 : 한국기후변화학회지 / 14권 / 6호 / 775 ~ 793페이지
· 저자명 : 최영현, 장용철, 염성찬, 신종석

초록

This study aims to identify the core values for climate change evaluation among various indicators by analyzing the degrees of multiplicity and similarity. A total of 1,421 indicators was collected from 16 indices used to measure Carbon Neutrality, Climate Change, Green Growth, and Sustainable Development. Of these, 1,267 codes were extracted based on keyword analysis using the conventional program MAXQDA 2022. Multiplicity was measured using the frequency of codes assigned to indicators, and similarity was measured using the sum of the number of indicators belonging to the same level. The keywords with high multiplicity were ‘energy,’ ‘emission,’ ‘climate,’ ‘resources,’ ‘transportation (traffic),’ and ‘electricity.’ Keywords of ‘energy,’ ‘emission,’ and ‘climate’ had high similarity and high multiplicity. On the contrary, the keywords ‘sustainability,’ ‘education,’ ‘population,’ ‘agriculture,’ and ‘gender equality’ had high multiplicity but low similarity. These results indicate the need to consider both multiplicity and similarity to identify core keywords for developing specific indices during the review of current climate indices and indicators. This study used a bottom-up approach to analyze indicators of various indices to identify the core values in climate change evaluation. The results of this study provide keyword information that can be useful in designing indices or associated indicators for climate change.

영어초록

This study aims to identify the core values for climate change evaluation among various indicators by analyzing the degrees of multiplicity and similarity. A total of 1,421 indicators was collected from 16 indices used to measure Carbon Neutrality, Climate Change, Green Growth, and Sustainable Development. Of these, 1,267 codes were extracted based on keyword analysis using the conventional program MAXQDA 2022. Multiplicity was measured using the frequency of codes assigned to indicators, and similarity was measured using the sum of the number of indicators belonging to the same level. The keywords with high multiplicity were ‘energy,’ ‘emission,’ ‘climate,’ ‘resources,’ ‘transportation (traffic),’ and ‘electricity.’ Keywords of ‘energy,’ ‘emission,’ and ‘climate’ had high similarity and high multiplicity. On the contrary, the keywords ‘sustainability,’ ‘education,’ ‘population,’ ‘agriculture,’ and ‘gender equality’ had high multiplicity but low similarity. These results indicate the need to consider both multiplicity and similarity to identify core keywords for developing specific indices during the review of current climate indices and indicators. This study used a bottom-up approach to analyze indicators of various indices to identify the core values in climate change evaluation. The results of this study provide keyword information that can be useful in designing indices or associated indicators for climate change.

참고자료

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