Blogs are one of the places on the web you can reliably find people's writing about their moods. Krisztian Balog presented a paper called "Decomposing Bloggers' Moods: Towards a Time Series Analysis of Moods in the Blogosphere." This can be used to produce interesting data. For example, MoodViews tracks a stream of mood-annotated text from LiveJournal. MoodViews tracks, predicts, and analyzes moods on blogs.
Moods have a cyclic component. Some moods depend on time of day, some on the day of week. You can show a correlation between major events (say the London Bombing) and mood. So far, there's less than a year's worth of data, so seasonal fluctuations are not included.
Blog posts that label themselves "stressed" show a slight drop in the summer and a huge spike before and then drop after Christmas. This is age dependent. Cheerful has a huge spike during the holidays. Annoyed shows a drop at the same time. Loved shows a peak at Valentines day.
Excited and Lonely are on the decline over the test period while Contemplative and Creative are on the rise. Stressed, Busy, and Working are all correlated.
Analyzing the gap between an expected mood and the actual mood can give an early indication that something is happening.
Future work will analyze other correlations between moods and look at longer periods.