Twitter confirms it: People tend to wake up in a good mood and are happiest on weekends.
The fast-paced forum is offering scientists a peek at real-time, presumably little-filtered human behavior and thoughts. Cornell University researchers turned to the microblog to study mood and found a pretty consistent pattern.
The researchers analyzed English-language tweets from 2.4 million people in 84 countries, more than 500 million of the brief, conversationlike exchanges sent over two years. They used a computer program that searched for words indicating positive mood -- "happy," "enthusiastic," "brilliant" -- or negative mood -- "sad," "anxious," "fear."
What they found: Unless you're a night owl, a positive attitude peaks early in the morning and near midnight, but starts to dip midmorning before rising again in the evening.
Aha, you might think, going to work and related hassles such as traffic explain that pattern. After all, there was more positive tweeting on the weekend, even though the morning peak of happy tweets occurred two hours later, probably because people slept late.
Not quite. Work-related stress may play a role, but it can't explain why that same midday dip occurs on the weekend, said researcher Scott Golder, a Cornell graduate student.
Instead, the pattern probably is due to the effects of sleep and our 24-hour biological clock, the so-called circadian rhythms that signal when it's time to sleep and to wake, Golder and Cornell sociologist Michael Macy reported. Their study appears in today's issue of the journal Science.
The researchers also examined tweets in the United Arab Emirates, where Friday and Saturday are considered the weekend. They found the same daily pattern, even though the workday tends to begin earlier there than in the West, and the same weekend pattern.
Previous research has linked the biological clock and mood, but was based mostly on small studies of American college students. There are cautions about studying Twitter postings, too: Their authors tend to be younger than the general population, and may be more affluent, better educated and different in yet-to-be-discovered ways.
Still, the study's bigger message is about the scientific potential of social media, Macy said. Other researchers have turned to Twitter to study political campaigning, to blog postings and Twitter feeds to study emotions, and to Google searches of flu symptoms to predict outbreaks.