Abstract
Live music concert analysis provides an opportunity to explore cultural and historical trends. The art of set-list construction, of which songs to play, has many considerations for an artist, and the notion of how much variety different artists play is an interesting topic. Online communities provide rich crowd-sourced encyclopaedic data repositories of live concert set-list data, facilitating the potential for quantitative analysis of live music concerts. In this paper, we explore data acquisition and processing of musical artists’ tour histories and propose an approach to analyse and explore the notion of variety, at individual tour level, at artist career level, and for comparisons between a corpus of artists from different musical genres. We propose notions of a shelf and a tail as a means to help explore tour variety and explore how they can be utilised to help define a single metric of variety at tour level, and artist level. Our analysis highlights the wide diversity among artists in terms of their inclinations toward variety, whilst correlation analysis demonstrates how our measure of variety remains robust across differing artist attributes, such as the number of tours and show lengths.
Original language | English |
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Journal | CEUR Workshop Proceedings |
Volume | 3834 |
Pages (from-to) | 802-828 |
ISSN | 1613-0073 |
Publication status | Published - 2024 |
Event | 2024 Computational Humanities Research Conference, CHR 2024 - Aarhus, Denmark Duration: 4. Dec 2024 → 6. Dec 2024 |
Conference
Conference | 2024 Computational Humanities Research Conference, CHR 2024 |
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Country/Territory | Denmark |
City | Aarhus |
Period | 04/12/2024 → 06/12/2024 |
Keywords
- computational musicology
- music information retrieval
- set-list composition
- statistical music analysis