Industry Planted: Investigation into the Promotion of Local Music Events using Content-Based Streaming Data

This thesis proposes and explores an adapted approach to music recommendation and event promotion, aimed at providing streaming users more accessibility to local artists, performers, and events. By focusing specifically on the enrichment of local music ecosystems, this research is undertaken with the express interest of local music artists, venues, and streamers in mind. It seeks to serve a multifaceted goal: revitalizing local music scenes by making them more visible and accessible through streaming platforms; empowering local music artists by providing them with a broader audience and new opportunities for engagement; reconnecting artists with the community, thereby fostering a stronger sense of local identity and cultural cohesion; and providing economic benefit to local venues through increased attendance and engagement. In essence, this thesis intends to harness the power of streaming platforms to rekindle the localized relationships between listeners, artists, and venues, thereby contributing to the renaissance, sustainability, and vibrancy of local music cultures. These outcomes will be achieved through a two-pronged theoretical and practical approach, incorporating Proof of Concept (PoC) algorithm with the Business Model Canvas (BMC). A Proof of Concept recommendation algorithm was developed as a tool to empirically demonstrate the viability of the proposed strategies. This prototype music recommendation algorithm was designed and tested with the explicit goal of creating a novel music recommendation algorithm that biased users towards exposure of smaller local artists and events.