Dance Hit Song Science
|Title||Dance Hit Song Science|
|Publication Type||Conference Proceedings|
|Year of Conference||2013|
|Authors||Herremans D., Martens D, Sörensen K.|
|Conference Name||International Workshop on Music and Machine Learning|
With annual investments of several billions of dollars worldwide, record companies can benefit tremendously by gaining insight into what actually makes a hit song. This question is tackled in this research by focussing on the dance hit song problem prediction 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. Different classifiers are used to build and test dance hit prediction models. The resulting model has a good performance when predicting whether a song is a ‘‘top 10'' dance hit versus a lower listed position.