earticle

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eal estate using the text mining technique. As a result of analyzing the first stage–regression model for the target period of five years, road width and the walking distance to the subway station were significant among the location factors. For the second step, text mining analysis was conducted. Through the analysis, it was found that the distribution and importance of major keywords were different before and after COVID-19. In the last three-stage model, Big Data by period, which is the result of the two-stage text mining analysis, was used as an independent variable to analyze the effect on the price of income-producing real estate traded for each period. As a result of the analysis, it was found that unstructured information such as online searches, reviews, and comments shows consumption trends and affects prices of income-producing real estate as well as industries. The forementioned findings could provide implications for effective investment strategies in the future reflecting on the factors affecting the price of income-producing real estate in the major trade area.