Abstract
This essay presents the results produced by the application of three corpus analysis tools to Thomas Pynchon’s Gravity’s Rainbow: word frequency/keyness analysis, social network analysis, and topic modeling. It uses these data to argue that the novel is peculiarly concerned with the concept of the present moment. Engaging along the way traditional arguments about the nature of the book’s Romanticism and its sense of “connectedness,” the essay demonstrates how distant reading can aid us in perceiving aspects of overwhelming texts that are not easy to perceive otherwise, consequently complementing rather than opposing close reading practices.
Highlights
In recent years, the wide availability of digitized literary works has given rise to a computational approach to analyzing these texts
We show that social networks allow characters to be categorized into roles based on how they function in the text, but that this approach is limited when using static social networks
In this paper we have motivated a computational approach to dynamic network analysis
Summary
The wide availability of digitized literary works has given rise to a computational approach to analyzing these texts. Our paper uses an annotation scheme that is welldefined and has been used in previous computational models that extract social events from news articles (Agarwal and Rambow, 2010). This computational model may be adapted to extract these events from literary texts. The focus of this paper is not to adapt the previously proposed computational model to a new domain or genre, but to first demonstrate the usefulness of this annotation scheme for the analysis of literary texts, and the social networks derived from it. We point certain limitations of the static network analysis and propose the use of dynamic network analysis for literary texts.
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