인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
This paper aims to propose a research framework of analyzing voting activities of a national assembly on the basis of member-level voting similarity and provides a case study in the 18<SUP>th</SUP> national assembly in South Korea. First, we propose a bill contentiousness measure that gives a higher score to bills for which ayes and noes are more diversified in both conservative and progressive parties. Based on the bill contentiousness measure, the top 5%, 10%, and 20% bills were identified and used for further analyses. Moreover, we propose a member-level voting similarity measure that compensates for the lower frequency of noes, and evaluate the pair-wise voting similarities for all lawmakers. Then, voting similarity differences to the affiliated/non-affiliated parties were analyzed for the members in the two major parties according to some internal/external key factors. Finally, similar voting groups were identified and their affiliations were investigated based on the multi-dimensional scaling (MDS) and network analysis techniques. A case study on the 18<SUP>th</SUP> national assembly of South Korea showed that the cohesion of the members in the ‘Hanara’ party becomes higher than that of the ‘Minju’ party as the bill contentiousness increases, whereas the number of elected, local constituency versus proportional representation, and the competition intensity in a local constituency were found to be partially influential to the voting activities of lawmakers. In addition, MDS and network analysis showed that there is a distinctive difference between two parties when all bills are analyzed, whereas the diversity of parties increases in the same group as the bill contentiousness increases.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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