Text Analysis and Literature Studies

The digital humanities emerged from text analysis and literature/literary studies.  Consequently, as literature and literary studies reside institutionally in English Departments, these departments have been the primary sites of DH innovations (Pressman & Swanstrom, 2013).  Some of the seminal DH projects and archives, such as The Victorian Web and The Walt Whitman Archive focus on literature, as do born digital archives, which contain materials that are not digitized but have always existed in digital form.

 

Digital humanities scholar Matthew Kirschenbaum, in his influential 2010 essay What is Digital Humanities and What’s It Doing in English Departments? (Kirschenbaum, 2016) suggests that two reasons that the digital humanities have focused on literature are that text, like numbers, is easy to manipulate digitally, and that computers and composition have had a symbiotic relationship for a long time.  Humanities computing (the term pre-dates “digital humanities”), with its emphasis on data processing and analysis, has benefited English literature scholarship in English, as well as literature in other languages.  Although the digitization and archiving of originally analog, non-digital resources constitutes a core activity, computational techniques are used for literary interpretation, enabled by the availability of large amounts of originally printed material in digital form, as, for instance, Project Gutenberg and Google Books.  The seemingly exponential growth of these projects brings the digital humanities into the orbit of “Big Data”.

 

This literary focus has been directed on text and words, the elemental unit of text and therefore literature.  Consequently, to some extent, literary studies are a data-driven discipline.  In addition to a focus on text, visualizations and computational algorithms are now often employed by literary scholars.  However, the scope of the “literary” can be expanded to include techniques and viewpoints for investigating the aesthetics and practices of literature, readers’ engagement with it, and literary criticism.  In this sense, the literary encompasses more than simply texts and words (Pressman & Swanstrom, 2013).

 

In digital culture, primacy is given to data and statistics, and in this way, argues digital humanities scholar Alan Liu, this data “transcends” historical and material contexts, and is not in need of interpretation.  However, Liu continues, this contrasts with the central tenets of literary studies, which emphasizes interpretation, argumentation, and meaning.  In traditional literary criticism, the underlying ideologies that underlie texts are analyzed and critiqued.

Close reading is one of the tools employed in literary criticism, wherein texts are carefully analyzed and contextualized, focusing on patterns and details.  The goal is to gain a deep understanding of the meaning of the text, and often the contexts and circumstances in which it was written.  Close reading has been, and remains, a key method in literary studies.  It does not require computational tools, although recent studies have discussed digital approaches that facilitate and enhance (rather than enable) close reading (Jänicke et al., 2015).
In contrast, distant reading, in which large amounts of text are analyzed at a “macroscopic” level, seeking patterns and insights from entire corpora, is much more computationally focused.  Distant reading utilizes (often highly interactive) visualizations and statistical and machine learning algorithms to perform large-scale analysis of multiple texts that would not be possible with close reading approaches.

Close reading and distant reading can complement each other.  Large scale patterns and trends can be detected with the computational techniques of distant reading.  Particularly interesting or unexpected features highlighted through distant reading can subsequently be analyzed in detail and contextualized in a fine-grained manner with close reading of some of the texts that were included in the larger-scale, coarse-grained, distant reading analyses.

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