토픽 모델링을 활용한 부동산 대책 및 사회적 이슈 분석

• 영문명: Exploring the Public Agenda of Real Estate Measures in Korea using A Topic Modeling Approach
• 발행기관: 한국부동산정책학회
• 저자명: 윤성진(Yun, Sungjin) 이관용(Lee, Kwanyong) 홍정기(Hong, Jung-Gi)
• 간행물 정보: 『부동산정책연구』제22집 제1호, 15~37쪽, 전체 23쪽
• 주제분류: 사회과학 > 정책학
• 파일형태: PDF
• 발행일자: 2021.06.20

영문 초록

This article synthesizes the numerous real estate measures taken by the Moon Jae-in administration of the Republic of Korea and the complex controversy surrounding them. The Korean government uses several policy measures in response to soaring housing prices, and these measures have been conducted under social context and created new disputes. Therefore, analyzing the trends in policy changes and social discussion behind them is necessary. In this context, we analyzed online news articles data through topic modeling, which is a text mining. Results show high interest in comprehensive measures, including loan regulation and tax policy, such as September 13, December 16, and June 17 measures. Although one measure included a number of policy points, the media has focused on specific issues such as “comprehensive real estate tax” in September 13 measure and “gap investment regulation” in June 17 measure. The topic modeling analysis identified 17 detailed topics under five categories: loan regulation, tax policy, public housing supply, private housing supply, and market response to measures. Moreover, some social debates not only show the previous conditions but also provide implications for future housing policy, such as preserving greenbelt zones, realization of official housing price for tax, and the balloon effect of the housing market.

목차

Ⅰ. 연구의 배경 및 목적

Ⅱ. 선행연구 검토

Ⅲ. 문재인 정부의 부동산 대책

Ⅳ. 실증분석

Ⅴ. 결론

참고문헌

키워드

부동산대책 토픽모델링 빅데이터 텍스트마이닝 LDA