Tesi, 2017, ENG

Predicting and explaining the popularity of songs with data mining

Campagna M.

University of Pisa, Pisa, Italy

Data mining techniques recently were used to solve several problems related to music. This dissertation studies songs popularity in order to find out factors that make a song popular or not. The outcomes obtained are also used to give an answer to the myth of four chords. This myth in fact asserts that all popular songs can be played by using only four chords. The entire project covers all the stages of Knowledge Discovery in the Databases<br>process. We aimed to make a first research on songs popularity. In particular, data on music songs are collected and studied. These data are also used to create several models using data mining techniques. The problem of predicting and explaining songs popularity is studied by using both regression and classification algorithms. Finally, the fittest model is interpreted and tested with specific instances in order to achieve the goal.

Keywords

data science, data mining

CNR authors

Pappalardo Luca

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 425777

Year: 2017

Type: Tesi

Creation: 2020-07-21 14:33:55.000

Last update: 2020-09-09 12:38:29.000

CNR authors

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:425777