Data Scraping YouTube for the Study of Lieder Reception

IF 0.2 3区 艺术学 0 MUSIC
Rachel E. Scott
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引用次数: 0

Abstract

A growing body of literature has shifted aesthetic attention from composition to performance, or the performing activity, and asserts that the act of performance creates meaning.1 Scholars have emphasized differences between the passive consumption and active making of – or even listening to – music.2 As I sought to understand the impact of performance on Alma Mahler's legacy, I identified the need to gather as much data as possible on who, what, where, when, why, and how her songs were performed. This need led me to evaluate the metadata associated with recordings of Alma Mahler's songs in the WorldCat union catalogue and the video sharing platform YouTube. Recent studies have shown the utility of leveraging big data for musicology, although few scholars have done so to investigate reception history. This essay outlines one approach to data scraping YouTube with emphasis on the value to those researching recent Lieder reception, and in doing so highlights some of the promise and limitations associated with web scraping.
YouTube上的数据抓取研究谎言接收
越来越多的文学作品已经将审美注意力从作曲转移到表演或表演活动上,并断言表演行为创造了意义。1学者们强调了音乐的被动消费和主动创作甚至聆听之间的差异。2当我试图理解表演对阿尔玛·马勒遗产的影响时,我发现有必要收集尽可能多的数据,说明她的歌曲是谁、什么、在哪里、何时、为什么以及如何表演的。这一需求使我评估了WorldCat联盟目录和视频共享平台YouTube中与Alma Mahler歌曲录制相关的元数据。最近的研究表明,利用大数据进行音乐学研究是有用的,尽管很少有学者这样做来研究接收历史。这篇文章概述了一种在YouTube上抓取数据的方法,强调了它对研究最近Lieder接收情况的人的价值,并强调了与网络抓取相关的一些前景和局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.30
自引率
66.70%
发文量
58
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