Music Connections is an Undergraduate Thesis project that explores the shared connections between the Billboard Year-End Singles (1946–2013). More than just eye candy, the goal is to prove that these types of network visualizations can show the structural, musical and cultural relationships between songs. By using a set of specific attributes combined with color identification, the graph can be used as an informational and interactive explorational tool.
A poster breaks down the data to be viewed from more of a statistical standpoint. That visualization, compared to the network graph, is better at showing trends and dominance of the selected categories for this project.
Additionally, one should be able to see the commonalities that a majority of these songs share with each other.
In order to have the best experience, please view the visualization on a laptop or desktop. It is not optimized for touch and mobile devices.
A network is a collection of points, called vertices, and a collection of lines, called arcs, connecting these points. A network is traversable if you can trace each arc exactly once by beginning at some point and not lifting your pencil from the paper. The problem of crossing each bridge exactly once reduces to one of traversing the network representing these bridges.
Data visualization is an objective representation of the data being presented. It is a means of making sense of complex data sets. Majority of the time, they are generated automatically through the use of algorithms or computer programs. The data is sometimes presented outside of its original context. The visualization itself builds the foundation for how it functions.
Without these tools and the amazing people that have developed them, this project would not have been possible.
Used to create the visualization.
For the code used to create the Sigma.Js template which was exported from Gephi.
Developed by Scott Hale.
Images displayed on this site are either Creative Commons use or created by me.