Decomposing Bloggers’ Moods Towards a Time Series Analysis of Moods in the Blogosphere

Using a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we provide a time series analysis of the number of blog posts annotated with a mood. State-space methods are used to determine decompositions of the time series data associated with bloggers’ moods (either individual or aggegrated), allowing us to look for patterns of trend, seasonality and cycle. Our analysis reveals a broad spectrum of phenomena: (i) there is a clear overall decline in the usage of mood annotations; (ii) weather phenomena and holidays have a clear impact on the profile of some moods; (iii) looking at the relative counts, we observe that some moods are stationary, while others decline or climb; and (iv) several moods display changes in their cyclical or seasonal component during the period covered by our data.