Using Social Media to Measure Labor Market Flows
Professor Margaret Levenstein (University of Michigan)
Professor Matthew Shapiro (University of Michigan)
Professor Michael Cafarella (University of Michigan)
Abstract: Social media enable new approaches to measuring economic activity and analyzing economic behavior at high frequency and in real time. This paper uses Twitter data to create indexes of job loss, search, and posting. Signals are derived by counting job-related phrases in Tweets. The indexes are constructed from the principal components of these signals. The University of Michigan Social Media Job Loss Index tracks initial claims for unemployment insurance, predicts 15 to 20 percent of the variance of the prediction error of the consensus forecast for initial claims, and provides greater signal regarding the true state of job loss.