Abstract

ABSTRACTIn recent years, advances in text annotation, the computational analysis of images and quantitative corpus linguistics have introduced new and exciting approaches to the study of text and paratext that combine the perspectives of historical linguistics and book history. However, so far most corpus-based research in this field has been hampered by the manual nature of the visual analyses (see, e.g., Tyrkkö, Marttila & Suhr 2013 and Tyrkkö 2013). The manual measuring and evaluation of visual features in a consistent manner is both slow and prone to human error, particularly with volumes of texts sufficient for statistical interrogation. As a result, while the linguistic analysis of historical texts can be rigorously systematic and corpus-based, the visual data, when taken into account at all, have typically been rather scarce and anecdotal in nature. In this paper, I will discuss new computational methods of analysing diachronic changes in visual features of title-pages and body text, and of combining that information with linguistic data. Using two linguistic corpora, Early Modern English Medical Texts and Late Modern English Medical Texts, and ImagePlot 1.1, a tool designed for the analysis of visual data, I will first map the paratextual features of the medical books and turn them into a matrix of statistically usable data points (Manovich 2012, 2013) for further processing.

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