Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper examines the information content of firm-specific sentiment extracted from Twitter messages. We find that Twitter sentiment predicts stock returns without subsequent reversals. This finding is consistent with the view that tweets provide information not already reflected in stock prices. We investigate possible sources of return predictability with Twitter sentiment. The results show that Twitter sentiment provides new information about analyst recommendations, analyst price targets and quarterly earnings. This information explains about one third of the predictive ability of Twitter sentiment for stock returns. Taken together, our findings shed new light on whether and why social media content has predictive value for stock returns.