Abstract
The study intends to understand whether the real estate sentiment index, calculated using real estate-related broadcasting news, has a significant correlation or causal relationship with the apartment sales price index based on data from 2012 to 2018 in the Seoul Metropolitan Area. We find that the broadcasting sentiment index correlates positively with the apartment sales price index; an increase in the broadcasting sentiment index results in an increase in the sales price index in Seoul, which again has a significant impact on the increase in the broadcasting sentiment index. In addition, the broadcasting sentiment index indicates a significant causal relationship between one-month and five-month time difference with the sales price index. The broadcasting sentiment index has a significant impact on the fluctuations in the apartment sales price index. It suggests that the mechanism of the real estate market can be explained and predicted by utilizing text mining and unstructured big data. It also implies that artificial intelligence techniques such as machine learning can be applied to the field of real estate.
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