  Is it possible use algorithms to find trends in the history of popular music?
And is it possible to predict the characteristics of future music genres? In
order to answer these questions, we produced a hand-crafted dataset with the
intent to put together features about style, psychology, sociology and
typology, annotated by music genre and indexed by time and decade. We collected
a list of popular genres by decade from Wikipedia and scored music genres based
on Wikipedia descriptions. Using statistical and machine learning techniques,
we find trends in the musical preferences and use time series forecasting to
evaluate the prediction of future music genres.
