Review of Martin J. Gliserman, Graphic Criticism: Semantics, Neurology and Cultural Transmission
DOI:
https://doi.org/10.15462/ijll.v12i1.162Abstract
Graphic Criticism: Semantics, Neurology and Cultural Transmission – A Study of 100 Classic Anglophone Novels, offers a new way to engage with familiar texts through data visualisation, thereby making a significant contribution to literary methodology. The book shifts between identifying longitudinal patterns in novels written and published between the eighteenth and twentieth centuries, offering close qualitative readings of these texts across four semantic categories: “Raw Universe, Human Body/Being, Built World, [and] Socially Constructed World” (19). Martin Gliserman’s approach demonstrates the ways in which canonical novels continue to generate new material and provides a method of analysis which could be extended by recent technological developments in text mining. Gliserman has long held a fascination with longitudinal research and the digital humanities but does not provide a precise date for this research project; it seems much of the data collection was undertaken in the 1990s and early 2000s (xxiv and 27). The book traces literary tradition(s) and variances over time, identifying the “constraints” operating on texts and through which the writer engages with the reader (38, original emphasis). Limited to one hundred novels, one might question the selection of the corpus which was to some extent dictated by the availability of digitised texts (27), and as a result many works fell outside the scope of this project. Meanwhile, the works of several authors have been included twice across the corpus (67). Increasing the size of the sample would strengthen the statistical evidence supporting Gliserman’s longitudinal observations. With freely accessible online databases of digitised texts, one could now introduce the same “conceptual hierarchies” (13-9) to a more extensive and representative collection of novels. Furthermore, automation through artificial intelligence technologies (AI) could streamline projects such as this, allowing visualisations to be produced at greater speeds, perhaps with greater specificity.