Jine Liu
ABSTRACT
To investigate the influence of real estate market subject sentiment and media sentiment on housing price changes, principal component analysis was used to construct a market subject sentiment index, and python was used to crawl microblogs for news reports related to housing prices and construct a microblog media sentiment index through text analysis. After the validity of each index was tested, a VAR model was built based on microblogging media sentiment and market subject sentiment, and the relationship between commodity residential price fluctuations and the related sentiment was analyzed using a combination of impulse response and variance decomposition methods. The results show that both the market subject sentiment index and the media sentiment index are highly correlated with the price of commodity residential properties, with a positive correlation between buyer and seller market sentiment and the price of commodity residential properties; media sentiment has a transient effect on the price of commodity residential properties.
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Index Terms
- The impact of Twitter media sentiment and buyer-seller market player sentiment on residential prices
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