Literary Data Mining: A review of Matthew Jockers, Macroanalysis: Digital Methods and Literary History (Urbana: University of Illinois Press, 2013).

被引:0
|
作者
Egan, Jim [1 ]
机构
[1] Brown Univ, Providence, RI 02912 USA
来源
DIGITAL HUMANITIES QUARTERLY | 2016年 / 10卷 / 03期
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中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
This review finds that Jockers' Macroanalysis provides a clear and provocative argument in favor of literary critics' use of data mining in their efforts to understand literary history. The review finds Jockers' case for a blended approach, one that combines data mining with close-reading techniques, compelling, and it finds, in addition, that his claim that such an approach holds the potential to revolutionize literary study to be a fair assessment of the possibities offered by data mining tools and techniques.
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页数:4
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