Can Twitter predict the stock market?

Researchers find that the Dow seems to correlate with 1 specific mood on Twitter.

By Kim Peterson Oct 15, 2010 2:18PM
frustrated © Comstock/JupiterimagesThere just might be a link between Twitter and the stock market.

That's the conclusion of researchers at Indiana University who studied the correlation between the public mood on the social-networking site and the movements of the Dow Jones Industrial Average.

The researchers studied Twitter messages posted over nearly 10 months in 2008, singling out those in which people talked about their moods.

The researchers placed the tweets into different categories based on the moods they expressed. Then they looked at whether there were similarities between those moods and the Dow.

Surprisingly, there was only one mood that seemed to move in parallel with the Dow: calm.

The calmness of the public could predict the Dow's movement, the researchers say. When people on Twitter were calm, the Dow surged. When people were not calm, the Dow dropped. Post continues after video:
There are huge holes in this study, many of which are pointed out by the authors themselves. They weren't able to narrow the tweets to a particular country, although back in 2008 much of the Twitter population lived in the U.S. That was an election year, which almost certainly skewed the Dow. Also, we don't know how accurately the mood on Twitter reflects that of the public at large.

Finally, we don't know why the public mood could affect the Dow. "One could speculate that the general public is presently as strongly invested in the DJIA as financial experts, and that therefore their mood states will directly affect their investment decisions and thus stock market values, but this too remains an area of future research," the researchers write. (The full text of the paper is here).

Not everyone is buying the finding. "This is almost certainly spurious," investor Paul Kedrosky writes about the research.

But Phil Pearlman at StockTwits loves the study. "I have observed qualitatively a possible relationship," he adds. "It provides a new potential framework for measuring near-real-time collective market sentiment that might be less encumbered by indecipherable motivations than current popular measures."

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