Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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} }
In 2024, China reported adding 16 million new users to its massive 1.1 billion internet population. The first half-year data in 2024 revealed that nearly half of the new internet users were between 10 and 18 years old, while a third were older adults aged above 50 years. The largest online community In 2023, China accounted for about one-fifth of the 5.5 billion internet users worldwide. However, compared to its total population, China’s internet penetration rate is lower than in other Asian countries. Penetration rates in both South Korea and Japan were extensively higher. The market potentials Internet usage in China is further characterized by a large regional discrepancy. In rural regions, the internet access rate is much lower than the national level. On the other side, the Chinese market became a mobile-first nation. Since 2014, more Chinese people have accessed the internet via mobile device than computers. The number of mobile internet users in China increased steadily over the previous decade.
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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} }