Using Twitter Language to Predict the Real Estate Market

EACL 2017 Mohammadzaman ZamaniH. Andrew Schwartz

We explore whether social media can provide a window into community real estate -foreclosure rates and price changes- beyond that of traditional economic and demographic variables. We find language use in Twitter not only predicts real estate outcomes as well as traditional variables across counties, but that including Twitter language in traditional models leads to a significant improvement (e.g. from Pearson r = :50 to r = :59 for price changes)... (read more)

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