Using the Echo Nest's automatically extracted music features for a musicological purpose

This paper sums up the preliminary observations and challenges encountered during my first engaging with the music intelligence company Echo Nest's automatically derived data of more than 35 million songs. The overall purpose is to investigate whether musicologists can draw benefit from Echo Nest's API, and to explore what practical and analytical consideration one should take into account when engaging with the numbers derived from the Echo Nest API. This paper suggests that the Echo Nest API hold a large potential of doing new types of analyses and visualizing the results. But it concurrently argues that a careful and critical approach is requisite, when interpreting the results.