Can Social Media Information Amplify Short-term Housing Price Changes? An Investigation in China’s Major Cities

Human economic activities are inherently embedded in social networks. Nevertheless, whether social media information can affect short-term housing price changes, one of the most fundamental economic elements in modern economies, remains unclear. In this paper, we empirically investigate the effect of public expectations expressed on social media on the short-term housing price fluctuations of cities in China. The data were collected from Sina Weibo, one of the largest Twitter-like services in China. We first use a lexicon-based method to mine public expectations of housing price on Sina Weibo, and then use panel econometric models to empirically verify whether the public expectations on Sina Weibo can help more effectively explain short-term housing price changes of cities in China. Our results suggest that housing price expectations expressed on social media have a positive effect on housing price changes; that is, a 0.1 increase in bullish expectations on social media will result in a 0.2% increase in the housing price growth rate monthly but lagged by two months. The results are robust after additional tests. Our results are theoretically and empirically consistent with the findings of behavioural economics in emphasizing the importance of expectations and the failure of economic fundamentals in explaining the short-term changes of urban housing prices, which can not only shed light on the amplifying role of social media information on housing price changes, but also help investors use information technologies to assist their investment decision-makings.