In the most recent reported fiscal year, Spotify generated approximately 13.82 billion euros in premium revenue and 1.85 billion euros in ad-supported revenue. Both figures were the highest reported to date, with premium revenue having grown by more than ten billion euros since 2017. Contributing to Spotify’s success was its strong global subscriber base – as of the third quarter of 2024, the music streaming platform had 252 million premium subscribers worldwide. Spotify has gained significant popularity across multiple markets, particularly in the United States, where over 26 percent of 18 to 34-year-olds reported using the service in 2018. Spotify’s competition Spotify’s closest competitor is Apple Music. That said, Apple’s worldwide subscribers are almost half that of Spotify’s, despite both services being popular for different reasons. Theoretically, Pandora Radio could have presented Spotify with a fair amount of competition, but this was not to be. Pandora’s radio station format failed to match Spotify’s playlist set-up in terms of popularity, and Pandora struggled to convert its users into paid subscribers, something which Spotify has always been good at. Pandora Radio received heavy investment from Sirius XM in 2017 and was officially acquired by the company in early 2019, so it will be interesting to see what happens in the future as Sirius gets to work on Pandora’s audience and attempts to generate cash from its arguably wide (but unpaid) user base. For now though, it seems that Spotify’s position remains safe.

Data on the amount of time spent listening to music in the United States in 2019 revealed that consumers spent an average of 26.9 hours per week enjoying their favorite tunes, down from 28.3 hours per week in 2018. Weekly consumption in 2017 was even higher at 32.1 hours.

MGD: Music Genre Dataset

Over recent years, the world has seen a dramatic change in the way people consume music, moving from physical records to streaming services. Since 2017, such services have become the main source of revenue within the global recorded music market. Therefore, this dataset is built by using data from Spotify. It provides a weekly chart of the 200 most streamed songs for each country and territory it is present, as well as an aggregated global chart.

Considering that countries behave differently when it comes to musical tastes, we use chart data from global and regional markets from January 2017 to December 2019, considering eight of the top 10 music markets according to IFPI: United States (1st), Japan (2nd), United Kingdom (3rd), Germany (4th), France (5th), Canada (8th), Australia (9th), and Brazil (10th).

We also provide information about the hit songs and artists present in the charts, such as all collaborating artists within a song (since the charts only provide the main ones) and their respective genres, which is the core of this work. MGD also provides data about musical collaboration, as we build collaboration networks based on artist partnerships in hit songs. Therefore, this dataset contains:

Genre Networks: Success-based genre collaboration networks

Genre Mapping: Genre mapping from Spotify genres to super-genres

Artist Networks: Success-based artist collaboration networks

Artists: Some artist data

Hit Songs: Hit Song data and features

Charts: Enhanced data from Spotify Weekly Top 200 Charts

This dataset was originally built for a conference paper at ISMIR 2020. If you make use of the dataset, please also cite the following paper:

Gabriel P. Oliveira, Mariana O. Silva, Danilo B. Seufitelli, Anisio Lacerda, and Mirella M. Moro. Detecting Collaboration Profiles in Success-based Music Genre Networks. In Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR 2020), 2020.

@inproceedings{ismir/OliveiraSSLM20, title = {Detecting Collaboration Profiles in Success-based Music Genre Networks}, author = {Gabriel P. Oliveira and Mariana O. Silva and Danilo B. Seufitelli and Anisio Lacerda and Mirella M. Moro}, booktitle = {21st International Society for Music Information Retrieval Conference} pages = {726--732}, year = {2020} }

MusicOSet is an open and enhanced dataset of musical elements (artists, songs and albums) based on musical popularity classification. Provides a directly accessible collection of data suitable for numerous tasks in music data mining (e.g., data visualization, classification, clustering, similarity search, MIR, HSS and so forth). To create MusicOSet, the potential information sources were divided into three main categories: music popularity sources, metadata sources, and acoustic and lyrical features sources. Data from all three categories were initially collected between January and May 2019. Nevertheless, the update and enhancement of the data happened in June 2019.

The attractive features of MusicOSet include:

• Integration and centralization of different musical data sources
• Calculation of popularity scores and classification of hits and non-hits musical elements, varying from 1962 to 2018
• Enriched metadata for music, artists, and albums from the US popular music industry
• Availability of acoustic and lyrical resources
• Unrestricted access in two formats: SQL database and compressed .csv files

|    Data    | # Records |
|:-----------------:|:---------:|
| Songs       | 20,405  |
| Artists      | 11,518  |
| Albums      | 26,522  |
| Lyrics      | 19,664  |
| Acoustic Features | 20,405  |
| Genres      | 1,561   |

According to a study on music consumption worldwide in 2022, younger generations tended to find new songs via music apps and social media, while older generations also used the radio as a format to discover new audio content.

The sales based on format of musical recordings for the record production and integrated record production and distribution industries, sound recording and music publishing (NAICS 512210 and 512220), for two years of data.

The summary statistics by North American Industry Classification System (NAICS) which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of record production and integrated record production/distribution (NAICS 512210 & 512220), music publishers (NAICS 512230), sound recording studios (NAICS 512240), and other sound recording industries (NAICS 512290), annual, for five years of data.

MuMu is a Multimodal Music dataset with multi-label genre annotations that combines information from the Amazon Reviews dataset and the Million Song Dataset (MSD). The former contains millions of album customer reviews and album metadata gathered from Amazon.com. The latter is a collection of metadata and precomputed audio features for a million songs.

To map the information from both datasets we use MusicBrainz. This process yields the final set of 147,295 songs, which belong to 31,471 albums. For the mapped set of albums, there are 447,583 customer reviews from the Amazon Dataset. The dataset have been used for multi-label music genre classification experiments in the related publication. In addition to genre annotations, this dataset provides further information about each album, such as genre annotations, average rating, selling rank, similar products, and cover image url. For every text review it also provides helpfulness score of the reviews, average rating, and summary of the review.

The mapping between the three datasets (Amazon, MusicBrainz and MSD), genre annotations, metadata, data splits, text reviews and links to images are available here. Images and audio files can not be released due to copyright issues.

MuMu dataset (mapping, metadata, annotations and text reviews)

Data splits and multimodal feature embeddings for ISMIR multi-label classification experiments

These data can be used together with the Tartarus deep learning library https://github.com/sergiooramas/tartarus.

NOTE: This version provides simplified files with metadata and splits.

Scientific References

Please cite the following papers if using MuMu dataset or Tartarus library.

Oramas, S., Barbieri, F., Nieto, O., and Serra, X (2018). Multimodal Deep Learning for Music Genre Classification, Transactions of the International Society for Music Information Retrieval, V(1).

Oramas S., Nieto O., Barbieri F., & Serra X. (2017). Multi-label Music Genre Classification from audio, text and images using Deep Features. In Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR 2017). https://arxiv.org/abs/1707.04916

This table contains 76 series, with data for years 2005 - 2011 (not all combinations necessarily have data for all years), and was last released on 2015-08-12. This table contains data described by the following dimensions (Not all combinations are available): Geography (6 items: Canada; Ontario; Quebec; Atlantic provinces ...), North American Industry Classification System (NAICS) (4 items: Record production and integrated record production/distribution; Sound recording studios; Other sound recording industries; Music publishers ...), Summary statistics (4 items: Operating revenue; Operating expenses; Operating profit margin; Salaries; wages and benefits ...).

Statistics illustrates consumption, production, prices, and trade of Music; printed or in manuscript, whether or not bound or illustrated in Georgia from 2007 to 2024.

A survey, conducted in the United States in October 2023, found that social media and user-generated content (UGC) are the main drivers for music discovery among Gen Z and Millennials consumers. That year, 82 percent of respondents from Generation Z and 70 percent among Millennials stated that they discovered music like this. These figures decrease significantly for older generations, for whom radio stations play a more important role for their music discovery.

Statistics illustrates consumption, production, prices, and trade of Music, printed or in manuscript, whether or not bound or illustrated in the World from 2007 to 2024.

Statistics illustrates consumption, production, prices, and trade of Music, printed or in manuscript, whether or not bound or illustrated in Reunion from 2007 to 2024.

Statistics illustrates consumption, production, prices, and trade of Music; printed or in manuscript, whether or not bound or illustrated in Cabo Verde from 2007 to 2024.

Statistics illustrates consumption, production, prices, and trade of Music, printed or in manuscript, whether or not bound or illustrated in Bolivia from 2007 to 2024.

The total sales of recordings based on nationality of artists for the record production and integrated record production and distribution industries, sound recording and music publishing (NAICS 512210 and 512220), for two years of data.

Music streaming revenue has increased astronomically in the last ten years alone – growing from 1.9 billion U.S. dollars in 2014 to 14,4 billion in 2023. Streaming has become a popular pastime for U.S. music fans and a major source of revenue for the industry, though many traditional consumers lament the resulting decline of physical music formats. Physical CD shipments have dwindled, whilst digital music platforms are flourishing.  The world of digital music   Platforms like Spotify have millions of users worldwide, and millions of tracks are streamed via the service each week. In the U.S., more than 25 percent of adults under the age of 35 are Spotify users, as well as almost 20 percent of adults aged 55 or above. Unsurprisingly, the vast majority of digital music revenue in the United States is derived from subscriptions and streaming, and successful musicians like Drake, Eminem, and Ariana Grande  amass billions of streams each year.  Whilst many artists in the music industry generate most of their income from touring, streaming is also incredibly lucrative, generating millions of dollars in earnings.  

Provide statistics table of the number of final teams in music competition over the years for individual category.

Music publishing royalties and rights by North American Industry Classification System (NAICS), for Canada, for one year of data.

Statistics illustrates consumption, production, prices, and trade of Music, printed or in manuscript, whether or not bound or illustrated in Monaco from 2007 to 2024.