In the last years music streaming services have taken over as the main mode of consumption for music, and even though they have noticeably contributed to the increase of profitability of the industry as a whole, it is still uncertain whether they facilitate the emergence of a more diversified and idiosyncratic musical environment or whether there is a tendency for market size and earnings to be skewed towards the most popular artists. This study intends to answer the following questions: what are the differences and similarities between the Top 100 most popular songs on YouTube, Spotify and Apple Music; and how evenly distributed is the consumption of the most popular artists and songs on these music streaming services? Using a dataset of the most popular songs for YouTube, Spotify and Apple Music collected from an online public database that aggregates data regarding the music industry in conjunction with variables operationalized and collected from the author, the paper will initially present some descriptive statistics and frequencies of the different characteristics of the songs and artists present within the Top Charts. The results find that there are mostly shared characteristics, especially in terms of the proportion of solo artists and bands, and that of song featurings, between Spotify and Apple Music, which also present the largest amount of overlapping songs within the Top100 charts, whereas YouTube was the most different from the others in terms of language, genre, and artist’s country of origin; which could indicate a larger market size and user base. The Second section of this paper will present an index of the most popular artists calculated by looking at the individual song rankings on each platform, finding a high concentration of songs and of rankings for the Top 10 artists. The final section of the paper will present the Gini Coefficient, an index of inequality of distribution of resources, for the popularity of the Top100 and Top2500 songs of each platform, as well as that for all the artists present on the various Top100 charts. The results show that whereas on the Top100 songs, the index of popularity is pretty equally distributed, this is quite different when looking at the Top2500 songs and the most popular artists, indicating that there is a high concentration of superstar artists.

Additional Metadata
Keywords Cultural Economics, Cultural Entrepreneurship, Music Streaming, Top Charts, Concentration, Diversity, Superstar Effect
Thesis Advisor C. Handke
Persistent URL
Series Cultural Economics and Entrepreneurship , Master Arts, Culture & Society
A. Moccia. (2019, June 11). All Musicians are Equal, but Some Musicians are More Equal than Others. Master Arts, Culture & Society. Retrieved from