Close-and Distant-Reading Modernism: Network Analysis, Text Mining, and Teaching the Little Review
摘要: 数字人文视域下的文学研究通常呈现出两种倾向:一种是对大规模数据集进行宏观层面的“远读”,另一种则是对单部作品的语言特性进行微观分析。其中,“大数据”项目利用软件对数百万卷期刊的出版数据或文学语料所构成的大规模数据集进行可视化处理,进而揭示出学者们单凭自身的穷尽式阅读难以获知的各种历史模式。然而,这类方法无法深度阅读文学文本。与此同时,基于文本挖掘的微观分析也呈现出类似的优缺点。因此,本章旨在探索一种融合之道,即综合运用这两种方法解读1918年9月刊的《小评论》。
Abstract: The digital humanities tends either to distant-read enormous data sets or to microanalyze the linguistic features of single works. “Big data” projects use software to visualize massive data sets of publishing information containing millions of volumes, revealing historic patterns that would be unobtainable by scholars. The main weakness of bigdata methodologies is their inability to read the works. The microscopic approach of text mining presents similar benefits and drawbacks. This article finds a middle ground by using these two techniques to read the September 1918 Little Review, examining the combined use of human markup and automated statistical techniques.
[V1] | 2024-05-07 09:50:29 | PSSXiv:202405.00446V1 | 下载全文 |
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