AN APPLICATION OF SOCIAL NETWORK ANALYSIS ON A RADIO STATION COLLECTION OF COUNTRY AND BLUEGRASS MUSIC
In his book The Algorithm Design Manual Skeina characterizes graphs as “…one of the unifying themes of computer science…”. (J. Scott & Carrington,2011) A graph is an abstraction and as such it can be a simplified representation of a system. Graphs can describe telecommunication systems, biological processes and systems of human interaction. Graphs that represent systems of human interaction are known as Social Networks. This thesis describes the creation of a social network from Country and Bluegrass artists who have played together on the same album. The data was gathered from a radio station database in 2013. Basic network and node metrics are gathered. The main cluster is then partitioned into communities using the Girvan Newman algorithm based on edge betweenness. Many top artists were identified using centrality measures and the communities were found to be related to music style.