IU Researchers: Twitter Can Help Predict Markets


This is just wild. According to Indiana University researchers, Twitter may be the greatest economic indicator yet: 

Researchers at IU Bloomington’s School of Informatics and Computing found the correlation between the value of the Dow Jones Industrial Average (DJIA) and public sentiment after analyzing more than 9.8 million tweets from 2.7 million users during 10 months in 2008.

Using two mood-tracking tools to analyze the text content of the large-scale collection of Twitter feeds, Associate Professor Johan Bollen and Ph.D. candidate Huina Mao were able to measure variations in public mood and then compare them to closing stock market values.

One tool, OpinionFinder, analyzed the tweets to provide a positive or negative daily time series of public mood. The second tool, Google-Profile of Mood States (GPOMS), measured the mood of tweets in six dimensions: calm, alert, sure, vital, kind, and happy. Together, the two tools provided the researchers with seven public mood time series that could then be set against a similar daily time series of Dow Jones closing values.

The researchers then correlated the two sets of values — Dow Jones and public mood — and used a self-organizing network model to test a hypothesis that predicting stock market closing values could be improved by including public mood measurements.

"We were not interested in proposing an optimal Dow Jones prediction model, but rather to assess the effects of including public mood information on the accuracy of the baseline prediction model," Bollen said. "What we found was an accuracy of 87.6 percent in predicting the daily up and down changes in the closing values of the Dow Jones Industrial Average."

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