Researchers from Harvard and Northeastern monitored three years of tweets to gauge how the mood of the country changes on a minute by minute basis.

Turns out, people are happiest in the early morning and late evening. (Because that's when they're not working? Please add your interpretation below). They're also happiest on Sunday mornings, and most depressed on Thursday afternoons.

Not surprisingly, this means the west coast gets happy three hours after the east coast.

Here's a time-lapse video showing a typical day. Red is grumpy, green is happy.

Here's the researchers' description of their efforts:

Mood Variations

A number of interesting trends can be observed in the data. First, overall daily variations can be seen (first graph), with the early morning and late evening having the highest level of happy tweets. Second, geographic variations can be observed (second graph), with the west coast showing happier tweets in a pattern that is consistently three hours behind the east coast.

Similar variations were discovered independently by Michael Macy and Scott Golder, and first reported in the talk "Answers in Search of a Question" at the New Directions in Text Analysis Conference in May 2010.

Weekly Variations

Weekly trends can be observed as well, with weekends happier than weekdays. The peak in the overall tweet mood score is observed on Sunday mornings, and the trough occurs on Thursday evenings.

About the Data and Visualization

The plots were calculated using over 300 million tweets (Sep 2006 - Aug 2009) collected by MPI-SWS researchers [1], represented as density-preserving cartograms. This visualization includes both weekdays and weekends; in the future, will we create seperate maps for each. The mood of each tweet was inferred using ANEW word list [2] using the same basic methodology as previous work [3]. County area data were taken from the U.S. Census Bureau, and the base U.S. map was taken from Wikimedia Commons. User locations were inferred using the Google Maps API, and mapped into counties using PostGIS and U.S. county maps from the U.S. National Atlas. Mood colors were selected using Color Brewer 2

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About Cartograms

A cartogram is a map in which the mapping variable (in this case, the number of tweets) is substituted for the true land area. Thus, the geometry of the actual map is altered so that the shape of each region is maintained as much as possible, but the area is scaled in order to be proportional to the number of tweets that originate in that region. The result is a density-equalizing map. The cartograms in this work were generated using the cart software by Mark E. J. Newman, available at http://www-personal.umich.edu/~mejn/cart.

Who We Are

We are researchers from Northeastern University and Harvard University, studying the characteristics and dynamics of Twitter.

Alan Mislove, College of Computer and Information Science, Northeastern University

Sune Lehmann, Center for Complex Network Research, Northeastern University

Yong-Yeol Ahn, Center for Complex Network Research, Northeastern University

Jukka-Pekka Onnela, Harvard Medical School, Harvard University

J. Niels Rosenquist, Harvard Medical School, Harvard University

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