Georges Patrick
Graduate School of Public and International Affairs, University of Ottawa, Social Sciences Building, Room 6011, 120 University, Ottawa, ON K1N 6N5 Canada.
Scientometrics. 2017;112(1):21-53. doi: 10.1007/s11192-017-2387-x. Epub 2017 Apr 22.
This paper proposes a statistical analysis that captures similarities and differences between classical music composers with the eventual aim to understand why particular composers 'sound' different even if their 'lineages' (influences network) are similar or why they 'sound' alike if their 'lineages' are different. In order to do this we use statistical methods and measures of association or similarity (based on presence/absence of traits such as specific 'ecological' characteristics and personal musical influences) that have been developed in biosystematics, scientometrics, and bibliographic coupling. This paper also represents a first step towards a more ambitious goal of developing an evolutionary model of Western classical music.
本文提出了一种统计分析方法,旨在捕捉古典音乐作曲家之间的异同,最终目的是理解为何某些作曲家即便“谱系”(影响网络)相似却“风格”迥异,或者为何“谱系”不同却“风格”相似。为此,我们运用了在生物系统学、科学计量学和文献耦合中所发展出来的统计方法以及关联度或相似度度量(基于特定“生态”特征和个人音乐影响等特征的有无)。本文也是朝着构建西方古典音乐进化模型这一更宏伟目标迈出的第一步。