Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
: what was communicated, who were listeners, and how they reacted. Using various natural language processing techniques, we identify the main topics discussed by the Fed and major audiences. While the Fed tweets talking about central banking topics attract greater attention from Twitter users, only the extensive margin is economically meaningful. Among all groups of users, the media accounts and economists are most active in engaging with the Fed, especially when discussing central banking-related issues. We also show that information extracted from the tweets can provide a real-time, qualitative diagnostic for inflation expectations and some reaction of these Twitter-based inflation expectations to policy action and communication.