Recent work in the sociology of taste has begun to grapple with the relational properties of traditional survey-based data using techniques inspired by network analysis. Despite productive results from this endeavor, critics rightly question the face and ecological validity of the vague macrogenre labels included in standard arts participation surveys (e.g., Classical, Rock, Rap) which feed into these novel methods. In this paper, I propose a link-clustering approach for discovering focused microgenres from standard survey-based information on cultural tastes, exploiting the underlying relational patterns realized by the indirect connectivity structure of genres (via people) in a two-mode network. The link-clustering approach partially answers two of the challenges of macrogenre critics: The fact that actual genres are overlapping and not crisply bounded and that there is hidden heterogeneity within the broad labels we usually focus on. To showcase the fruitfulness of the proposed approach, I engage in two “case studies” featuring the vague macro genres of “Heavy Metal” and “Latin/Salsa” music and show the focused microgenres produced by the link clustering procedure are segmented in ways that help resolve puzzles that have emerged in previous work.

中文翻译：

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通过关系从宏观流派到微观流派

品味社会学的最新工作已经开始使用受网络分析启发的技术来解决传统的基于调查的数据的关系属性。尽管这一努力取得了丰硕的成果，但批评家正确地质疑了标准艺术参与调查（例如古典、摇滚、说唱）中包含的模糊宏观流派标签的面貌和生态有效性，这些标签为这些新颖的方法提供了依据。在本文中，我提出了一种链接聚类方法，用于从基于标准调查的文化​​品味信息中发现重点微流派，利用两种模式网络中流派（通过人）的间接连接结构实现的潜在关系模式。链接聚类方法部分回答了宏观流派批评家面临的两个挑战：实际流派是重叠的且界限不明确，而且我们通常关注的广泛标签中存在隐藏的异质性。为了展示所提出的方法的成果，我进行了两个“案例研究”，以“重金属”和“拉丁/萨尔萨”音乐的模糊宏观流派为特色，并展示了链接聚类过程产生的重点微观流派的分割方式：帮助解决以前工作中出现的难题。