My paper analyzed collaboration networks between musicians on YouTube in an effort to show that YouTube is democratizing creative processes. This data was collected in mid-March of 2011 using data from the YouTube channels of the top 100 most- subscribed musicians during that time period. Artists were separated into two categories: “Homegrown” and “Commercial.” Loosely defined, “Homegrown” artists are ones who start their careers on YouTube, while Commercial artists are generally established artists who are signed to major record labels. Within the top-100 most-subscribed musicians, artists were fairly evenly divided into the homegrown and commercial categories. Data about all the available videos was collected and then analyzed for collaborations. Collaborations were defined either as two or more artists working together to record a song or as artists working together to produce a video (which then included some connections between musicians and YouTube music video producers). The three attached graphs show 1) Collaborations between Homegrown YouTube artists, separated by connected components (260 vertices), 2) Collaborations between Commercial YouTube artists, separated by connected components (70 vertices), and 3) Collaborations between both Commercial and Homegrown artists, separated by connected components. All graphs were arranged using the Harel-Koren Fast Multiscale Algorithm on NodeXL. Using qualitative analysis and data from the networks themselves, I was able to determine that 1) the largest connected subgraph within the Homegrown collaboration network is larger and denser than the largest connected subgraph within the Commercial artist collaboration network and 2) that the Homegrown collaboration network displays more small world properties than the Commercial artist collaboration network.