Traces of the Old, Uses of the New

Abstract

Digital Humanities remains a contested, umbrella term covering many types of work in numerous disciplines, including literature, history, linguistics, classics, theater, performance studies, film, media studies, computer science, and information science. In Traces of the Old, Uses of the New: The Emergence of Digital Literary Studies, Amy Earhart stakes a claim for discipline-specific history of digital study as a necessary prelude to true progress in defining Digital Humanities as a shared set of interdisciplinary practices and interests. Traces of the Old, Uses of the New focuses on twenty-five years of developments, including digital editions, digital archives, e-texts, text mining, and visualization, to situate emergent products and processes in relation to historical trends of disciplinary interest in literary study. By reexamining the roil of theoretical debates and applied practices from the last generation of work in juxtaposition with applied digital work of the same period, Earhart also seeks to expose limitations in need of alternative methods—methods that might begin to deliver on the early (but thus far unfulfilled) promise that digitizing texts allows literature scholars to ask and answer questions in new and compelling ways. In mapping the history of digital literary scholarship, Earhart also seeks to chart viable paths to its future, and in doing this work in one discipline, this book aims to inspire similar work in others.

Overcoming deep web challenges: Sustainable solutions for digital age information seekers

“…At the forefront of this mission lies the technique of web scraping, much like skilled archaeologists carefully extracting data from websites. Through the adept use of specialized scripts and software, users can systematically uncover concealed fragments of information, contributing to a better comprehension of the constantly evolving content within the deep web (Earhart, 2015). As we navigate this digital landscape, the practice of data crawling emerges as an equally significant tool.…”

On Making in the Digital Humanities

“…Next to this work, scholars have been pushing forward our understandings of other, less-examined aspects of the history of DH (writ large) too. These include discipline-specific studies of the early years of digital literary scholarship (Earhart 2015) and digital history (Crymble 2021); studies of scholars who made largely overlooked contributions to DH ; studies of the emergence of scholarly associations, for example in Canada (Gouglas et al 2013); studies of the field's central platforms for information and knowledge dissemination and creation, like Humanist (Nyhan 2016); outlines of the field's attitudes to the establishment of processes like peer review (Nyhan 2020); and studies of the portrayal of computing during the early phase of the field of humanities computing in the major Canadian newspaper Globe and Mail (Rockwell et al 2011).…”

Humanistic interpretation and machine learning

“…In their view, the problem with established interpretive methodology is that this influence is often implicit and not recognized, and thus the preconceptions that guide analysis cannot be subjected to rigorous empirical scrutiny. In this sense, computational methods might be superior to traditional close reading-and by extension, perhaps also to coding-based analyses-because their particular biases might be easier to detect than those embedded in established interpretive practices (Earhart 2015). Thus, the emerging debate about computational methods for text analysis provides a space for critically assessing the biases of interpretive practices of humanistic scholarship more broadly.…”