Can You Really Predict Markets With Twitter?

In this paper, I attempt to apply an emotional proxy derived by applying the Affective Norms for English Words (ANEW) to messages posted to the Twitter social networking service in order to forecast the movement two stock market indices: the Dow Jones Industrial Average (DJIA) and the CBOE Volatility Index (VIX). In contrast to previous works, I have compared the results of various forecast models employing different sentiment variables, as well as comparing the neural network approach to more standard logistic re- gression. Additionally, several of the models used employ an as-yet unique sentiment proxy, focusing on the average of expressed emotion rather than the volume of expressed emotion. The results indicate that while there is a distinct possibility that sentiment variables can assist in accurately forecasting market movement, the differences in choice of sentiment proxy and forecast method are less important than anticipated