论文标题
管弦乐音乐会编程网络分析
Network Analysis of Orchestral Concert Programming
论文作者
论文摘要
管弦乐音乐会节目是一项具有挑战性但至关重要的任务，可以扩大观众的参与度，通常是由定性的启发式方法和共同的音乐实践驱动的。管弦乐节目的定量分析是有限的，但是随着许多乐团在线归档其性能历史，已经变得更有可能。这项工作的贡献是使用统计网络模型来定量探索管弦乐音乐会编程，重点介绍哪些因素决定了波士顿交响乐团在同一音乐会中是否将两个作曲家编程在一起。我们发现，组成的类型是确定哪些作曲家一起执行的最重要的协变量，并且从管弦乐编程的角度来看，添加剂和乘法效果是合乎逻辑的。这些结果表明，网络分析是对音乐会编程进行分析的有前途的方法，并有多个指示将来扩展。
Orchestral concert programming is a challenging, yet critical task for expanding audience engagement and is usually driven by qualitative heuristics and common musical practices. Quantitative analysis of orchestral programming has been limited, but has become more possible as many orchestras archive their performance history online. The contribution of this work is to use statistical network models to quantitatively explore orchestral concert programming, focusing on which factors determine if two composers are programmed together in the same concert by the Boston Symphony Orchestra. We find that the type of composition is the most important covariate in determining which composers are performed together and the additive and multiplicative effects are logical from an orchestral programming perspective. These results suggest that a network analysis is a promising approach for the analysis of concert programming, with several directions for future extensions.
