NEW YORK (Reuters Life!) - Twitter is for more than just tweeting.

Using millions of Twitter messages, or tweets, from the popular social networking site, researchers at Northeastern University in Boston have created a Twitter Mood Map to measure the moods of the nation.

People are happiest in the morning and in the evening, with happiness peaking on Sunday morning and dipping Thursday night, they found. Twitter users appeared most gloomy at mid-afternoon, shifting to better moods in the evening.

Not surprisingly, people appeared happier on the weekends, with residents of California, Miami and southern states among the most content, they learned.

A colorful time-lapse video on the website http://www.ccs.neu.edu/home/amislove/twittermood/ shows the happy moods pulsating from the U.S. east coast to the west coast and back again.

The researchers are the first to admit the findings are not terribly scientific -- Twitter users tend to be tech-savvy, live in large cities and are a fraction of the total population -- but according to the results they have potential as a tool for providing real-time analysis of critical issues.

Even though individual tweets are pointless to anyone besides your followers, in aggregate there is a lot of meaningful information that can be an instrument to see how people feel about things, whether it's public reaction to a politician's speech or a consumer attitudes about a brand, said Sune Lehmann, one of the researchers.

Lehmann and others used a psychological word-rating system to analyze key words in some 300 million Twitter messages as happy or sad. They then created maps based on the location of the messages and the general moods they evoke.

The map could be useful not only to collect public opinion but to mobilize users quickly, such as in a drive for emergency relief donations.

The potential there is tremendous, on both an individual and societal level, said Johan Bollen, a computer scientist at Indiana University not involved in the project. It's absolutely crucial to have real-time indicators about how the public feels, not in months, but in a matter of hours and days.