It is well known that news can affect the psychological factor and sustain the housing bubble by framing specific information about the housing market. The news reports about real estate market could affect an expectation of housing consumers which is one of the significant factors to explain housing market trends. To explore the relationship among housing market news, consumers' sentiment, and market trends, we develop a Media Tone Index based on housing news articles collected from the online portal site. We apply text-mining techniques to quantify the tones of news articles related to the housing market. Then, we conduct time-series analysis such as Autoregressive Distributed Lag and Error Correction (ARDL-EC) models to analyze the dynamic relationship between the Media Tone Index and housing market trends in South Korea. As a result, we identify similar time-series trends between the Media Tone index and consumers' sentiment. Moreover, when the housing market was on a downtrend, news articles' tone tended to become positive. The relationship between the Media Tone Index and other housing market variables identified in this study could provide a better understanding of housing market dynamics both in the short- and long-term.