An analysis  by Johan Bollen at Indiana University and associates of almost 10 million tweets from 2008 shows how they can be used to predict stock market movements up to 6 days in advance.

One algorithm, called the Google-Profile of Mood States (GPOMS), records the level of six states: happiness, kindness, alertness, sureness, vitality and calmness.

The question that Bollen and associates ask is whether any of these states correlates with stock market prices.

So they took 9.7 million tweets posted by 2.7 million tweeters between March and December 2008 and looked for correlations between the GPOMS indices and whether Dow Jones Industrial Average rose of fell each day.

Their extraordinary conclusion is that there really is a correlation between the Dow Jones Industrial Average and one of the GPOMS indices–calmness.

Ref: arxiv.org/abs/1010.3003: Twitter Mood Predicts The Stock Market