This study investigates the interdependent relationships between the stock market and economic news in the U.S. context. 2,440 economic tweets from Reuters and Bloomberg published in September 2015 were analyzed within short-term intervals (5 minutes, 20 minutes, and 1 hour) as well as 50 influential Bloomberg market coverage stories distributed via their terminals for the same period of time. Using Vector Auto Regression analyses, it was found that news volume, news relevance, and expert opinion in tweets seem to influence the fluctuation of the Dow Jones Industrial Average (DJI) positively, while economic news appears to respond to market fluctuation with less coverage, including fewer retweets, favorites, updates, or expert opinions conveyed. Inspecting the influential market stories by Bloomberg, the results imply that while Bloomberg terminals provide firsthand information on the market to professionals, tweets rather seem to offer follow-up reporting to the public. Furthermore, given that the effect of economic tweets on the DJI fluctuations was found to be strongest within longer time intervals (i.e., 1 hour), the findings imply that public traders need more time to evaluate information and to make a trading decision than professional investors.