In lieu of an abstract, here is a brief excerpt of the content:

  • American Studies + Computational Humanities
  • Lauren Tilton (bio)

Recounting her experience at the 2008 annual conference of the American Studies Association, Tara McPherson observed that attendees were suspicious of computational work. They "perceiv[ed] it to be complicit with the corporatization of higher education or as primarily technological rather than scholarly," she argued.1 Arguments continue to circulate that computational work—whether in the form of articles, digital projects, or tools—is merely technological positivism, often in the service of neoliberalism. Daniel Allington, Sarah Brouillette, and David Golumbia's polemic in the Los Angeles Review of Books, for example, argues that digital humanities is actively facilitating the neoliberal takeover of the university by supporting a field that is simply training students in technology skills for industry. Such articles have turned into a cottage industry, too often ignoring the critical lens with which many scholars engage in this work while perpetuating a myth that only specific areas of inquiry are inculcated in or resisting neoliberalism's logic.2 The perniciousness of such narrow critiques is augmented by how these articles render invisible the important work, particularly by women and scholars of color, to use and critique computational techniques to study topics such as race, gender, and even neoliberalism itself. This is not to say that hesitation or critique is unwarranted, but the minimal engagement with and often quick dismissal of computational techniques elicit concern about even experimenting with computational analysis.3 Such a response is even more surprising from a field so often open to methodological change.

The tide is shifting.4 Scholars are engaged in developing a critical computational humanities shaped by American studies. Computation offers a methodology for studying culture. At the same time, questions about culture provide a critical lens through which to analyze computation. Such generative tension is resulting in exciting work at the intersection of the two fields. But first, let us define our terms.

What does it mean to say computation and computational humanities? Computation is the process of using computers to calculate an output given [End Page 633] an input. The breadth of such a process includes computing at a multitude of scales from counting in a program like Excel to running a task that requires high-performance computing. As Stephen Ramsay argues, computers are designed for "enumeration, measurement, and verification" and provide a powerful analytic tool when paired with critical inquiry.5 The term computational humanities has emerged to suggest the use of computing for large-scale analysis of humanities data. Processing data that exceed what individuals can analyze on their own involves a form of counting or the use of an algorithm through a tool or programming language. While often commonly positioned at the intersection of computer science and digital humanities, computational humanities engages with other fields including data science, (computational) linguistics, and statistics.6 Such a transdisciplinary approach creates "a digital ecology of data, algorithms, metadata, analytical and visualization tools, and new forms of scholarly expression that result from this research," as Christa Williford and Charles Henry, of the Council on Library and Information Resources, write.7

Text analysis, particularly the method of topic modeling, has enjoyed broad exposure within computational humanities. However, areas such as spatial analysis, network analysis, and image analysis are becoming increasingly prominent as scholars question the continued focus on text. This shift is being driven by scholars from fields like American studies, who have long argued that to understand culture requires analyzing forms other than text and word culture, and responded by developing methods in conversation with fields like material culture studies, sound studies, and visual culture studies. The result is a growing number of terms used to describe these approaches such as cultural analytics, distant listening, distant reading, distant viewing, and macroanalysis.8 All signal computational analysis at scale of different kinds of corpora including images, time-based media, sound, and text.

Data. Scale. Distance. Algorithm. Speed. Fast-forward a decade, and these terms continue to cause significant uneasiness among humanists, particularly among American studies scholars. Computational humanities has been at the center of digital humanities debates in fields like literary studies, yet remains seemingly peripheral to our field. This is intriguing given that some of...