Abstract

In recent years, housing prices in major cities in China have generally maintained an upward trend, and housing prices have remained high for a long time. China’s economic growth has its own particularity in the world, and the real estate market as a major support point for the economy, its future development is crucial to the economy. Taking Guangzhou as an example, this paper uses text mining method to extract media influence from media texts, and constructs the buyer confidence index, and uses it as a proxy variable for buyers’ mental expectations. This article finally obtained a total of 115,139 articles on the housing market, forming an article pool for text mining. In the study and analysis of the explanatory effect of the home buyer confidence index on housing prices, this paper uses multiple linear regression to analyze the main factors affecting housing prices, and concludes that buyers’ sentiment is significantly positively correlated with house prices.

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