| Summary: | 碩士 === 國立臺灣大學 === 經濟學研究所 === 107 === The paper investigates the causal relations between the public sentiments and the housing market in Taiwan. Instead of using survey data to measure the sentiments like most of the studies, the paper constructs the sentiment indices by narrative analytical methods. We scrape more than 1.6 million posts from Mobile01, which is one of the biggest social media forums in Taiwan. As the ternary support vector machine (SVM) model outperforms other machine learning models in our data, it is used for predicting the sentiments of the posts. Through Granger causality test, we find three different causal relations. First, quantities Granger-cause house prices. Second, quantities Granger-cause the sentiments. Finally, the sentiments Granger-cause house prices. The results of these unilateral Granger causalities provide a hint for the mechanism of how transaction volumes affect house prices.
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