The Mellon-funded Visualizing English Print (VEP) project joins computer scientists and literary scholars to scale textual analysis and visualization to increasingly large corpora, beginning with the early modern period. It strives to make early modern texts accessible for computational analysis. Furthermore, its purpose is to design tools to support the workflow of humanist scholars.
Capitalizing on the similarities of humanist and computational methods, the VEP project practices scalable scholarship, which entails the study of objects across varying levels of scale to detect patterns. Close reading, a humanist method of inquiry, involves deliberate, attentive reading at multiple levels of a text with the goal to interpret how ideas unfold. Close reading identifies patterns at different textual levels, such as syntax, imagery, and structure. The identification of patterns similarly fuels computational analysis. Algorithms for textual analysis are coded to detect patterns for our inspection. Texts can be thought of as data upon which we can perform abstraction, formalization, and statistical inference. While computational text analysis (automated reading) cannot replace close reading, it can supplement humanist inquiry by locating patterns at scales and across scales not feasible for human readers.