텍스트마이닝을 활용한 부동산 시장 인식 변화 연구

Abstract

This study compared and analyzed real estate market trends over the last six years using social big data generated on the web and social media. To this end, the applicability of social network analysis as a method of confirming and understanding public perception of the real estate market was confirmed. Big data were used for analysis, and because keyword network analysis was at the heart of the study, the author's patented “emotional information analysis method” was partially used. The analysis result reveals that from 2017 to 2019, keywords related to the rising phase of the real estate market were derived with high influence, and real estate policy keywords were ranked highly. Meanwhile, from 2020 to 2022, keywords related to the real estate market downturn had a high impact, and those related to real estate costs were ranked high. These research findings are a preliminary study that seeks an effective research methodology in understanding the past and present real estate markets. More specific policy research should be conducted using these research results.