Textmining에 의한 부동산 빅데이터 감성분석 모형 개발

다국어 초록 (Multilingual Abstract)

As a new paradigm, big data provides a technology that helps predict the future and overcome difficult issues. In the Real Estate market, which is based on a complex mechanism, there were limitations in using structured data for analysis and prediction. Big data is expected to help overcome such limitations by using analysis techniques that includes unstructured data and produce information that can create new values. This study aimed to propose a model that can help diagnose the Real Estate market and predict Real Estate prices. In the proposed model, news articles related to Real Estate (unstructured data) are collected by using web crawling, and the data are quantified via sentiment analysis. And then, in the study, the effectiveness of the proposed sentiment model was verified by strong correlation between the data found in the sentiment analysis and the real sale prices disclosed by Ministry of Land, Infrastructure and Transport. Therefore, future research may be able to use the proposed sentiment analysis model for making decisions related to Real Estate.