  Record companies invest billions of dollars in new talent around the globe
each year. Gaining insight into what actually makes a hit song would provide
tremendous benefits for the music industry. In this research we tackle this
question by focussing on the dance hit song classification problem. A database
of dance hit songs from 1985 until 2013 is built, including basic musical
features, as well as more advanced features that capture a temporal aspect. A
number of different classifiers are used to build and test dance hit prediction
models. The resulting best model has a good performance when predicting whether
a song is a "top 10" dance hit versus a lower listed position.
