Data for a Deeper Understanding
By aggregating historical and current data from Billboard, Spotify, Shazam, Apple Music, and iTunes, and more, MusicID is an all-in-one platform that has revolutionized music research. We are often asked how the data of our platform can be used. The case studies below illustrate only some of the endless applications.
MusicID is much more than raw sets of numbers. Read a few of our short case studies and learn how MusicID's built-in visualisation tools help researchers to make startling insights quickly and easily, with only a few clicks.
- Variance of the Life Cycle of # 1 Singles on the Billboard Hot 100 Chart from the 1960s to 2010s.
- See the exact week hip-hop broke into the mainstream.
- The Beatles vs. Musicals: What was even bigger than Beatlemania?
- In 2007 Radiohead parted ways with their record label, EMI. The label had agreed to be purchased by private equity firm Terra Firma that same year. Subsequently, the band self-released their following album In Rainbows on a direct to consumer, pay-what-you-want model via download on their website.
Using MusicID, you can easily find the answers to such questions as:
See what was not visible before MusicID’s groundbreaking platform revealed the full story!
Exciting Work Already Being Done Using MusicID
Steven Braun, Data Analytics and Visualization Specialist at Northeastern University, used data from MusicID to create a visual representation of the crossover success of American, British, and Japanese artists on their respective singles charts.
Dr. Richard Florida, University of Toronto Professor and Senior Editor at The Atlantic, and Patrick Adler, a Ph.D. student at UCLA, used data provided by Music ID to identify the 50 top-selling artists between 1950 to 2014. They then used this information to create a locational database in order to determine which cities produced pop’s biggest hit-makers.
Our partners at Queen Mary University of London have brought together evolutionary biologists and computer scientists to study the evolution of pop music using data from Music ID.