  The consumption history of online media content such as music and video
offers a rich source of data from which to mine information. Trends in this
data are of particular interest because they reflect user preferences as well
as associated cultural contexts that can be exploited in systems such as
recommendation or search. This paper classifies songs as seasonal using a
large, real-world dataset of user listening data. Results show strong
performance of classification of Christmas music with Gaussian Mixture Models.
