A new sharemarket index indicator, the sentiment on Twitter

Friday, 22 October, 2010

Analysing the mood of Twitter users, based on their tweets, can be used with some accuracy in predicting values of the Dow Jones Industrial Average, the US stock market index, up to as much as six days in advance, after a correlation between the Dow’s values and the general mood of tweets recently came to light.

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.

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