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Consumer spending is a vital macroeco- nomic indicator. In this paper we present a novel method for predicting future con- sumer spending from social media data. In contrast to previous work that largely re- lied on sentiment analysis, the proposed method models consumer spending from purchase intentions found on social media. Our experiments with time series analy- sis models and machine-learning regres- sion models reveal utility of this data for making short-term forecasts of consumer spending: for three- and seven-day hori- zons, prediction variables derived from so- cial media help to improve forecast ac- curacy by 11% to 18% for all the three models, in comparison to models that used only autoregressive predictors.

Forecasting Consumer Spending from Purchase Intentions Expressed on Social Media