Collected from: Monitoring how Twitter users are feeling can predict the stock market three days in advance | Mail Online
Analyzing almost 10 million tweets, research finds public mood can predict Dow days in advance: IU News Room: Indiana University
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.
A graph of Dow Jones Industrial Average values (center, blue) and tweets identified with a "calm" mood during a time series (bottom, red) running three days prior are overlaid in the top graph to show gray areas of significant overlap.
Collected from: Analyzing almost 10 million tweets, research finds public mood can predict Dow days in advance: IU News Room: Indiana University
- Sources
- How monitoring how Twitter users are feeling can predict the stock market three days in advance | Mail Online
- Analyzing almost 10 million tweets, research finds public mood can predict Dow days in advance: IU News Room: Indiana University
- YouTube - Informatics Professor Shows Link Between Tweets and Stocks
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