Although digital humanities (DH) has received a lot of attention in recent years, its status as “a discipline in its own right” (Schreibman et al., A companion to digital humanities (pp. xxiii–xxvii). Blackwell; 2004) and its position in the overall academic landscape are still being negotiated. While there are countless essays and opinion pieces that debate the status of DH, little research has been dedicated to exploring the field in a systematic and empirical way (Poole, Journal of Documentation; 2017:73). This study aims to contribute to the existing research gap by comparing articles published over the past three decades in three established English-language DH journals (Computers and the Humanities, Literary and Linguistic Computing, Digital Humanities Quarterly) with research articles from journals in 15 other academic disciplines (corpus size: 34,041 articles; 299 million tokens). As a method of analysis, we use latent Dirichlet allocation topic modeling, combined with recent approaches that aggregate topic models by means of hierarchical agglomerative clustering. Our findings indicate that DH is simultaneously a discipline in its own right and a highly interdisciplinary field, with many connecting factors to neighboring disciplines—first and foremost, computational linguistics, and information science. Detailed descriptive analyses shed some light on the diachronic development of DH and also highlight topics that are characteristic for DH.

中文翻译：

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数字人文学科——本身就是一门学科？数字人文在学术格局中的作用和地位分析

尽管近年来数字人文 (DH) 受到了很多关注，但它作为“一门独立学科”的地位（Schreibman 等，数字人文的伴侣（pp. xxiii–xxvii）。Blackwell；2004）其在整个学术领域的地位仍在谈判中。尽管有无数文章和观点争论 DH 的地位，但很少有研究致力于以系统和实证的方式探索该领域（Poole，Journal of Documentation；2017:73）。本研究旨在通过比较过去三十年在三个成熟的英语 DH 期刊（Computers and the Humanities、Literary and Linguistic Computing、Digital Humanities Quarterly）包含来自其他 15 个学科的期刊的研究文章（语料库大小：34,041 篇文章；2.99 亿个代币）。作为一种分析方法，我们使用潜在 Dirichlet 分配主题建模，结合最近通过层次凝聚聚类聚合主题模型的方法。我们的研究结果表明，DH 本身既是一门学科，又是一个高度跨学科的领域，与相邻学科有许多联系因素——首先是计算语言学和信息科学。详细的描述性分析揭示了 DH 的历时发展，并突出了 DH 特有的主题。结合最近通过层次凝聚聚类聚合主题模型的方法。我们的研究结果表明，DH 本身既是一门学科，又是一个高度跨学科的领域，与相邻学科有许多联系因素——首先是计算语言学和信息科学。详细的描述性分析揭示了 DH 的历时发展，并突出了 DH 特有的主题。结合最近通过层次凝聚聚类聚合主题模型的方法。我们的研究结果表明，DH 本身既是一门学科，又是一个高度跨学科的领域，与相邻学科有许多联系因素——首先是计算语言学和信息科学。详细的描述性分析揭示了 DH 的历时发展，并突出了 DH 特有的主题。