Computational History of Modernism

Patterns Taken for Wonder: A Computational History of Modernism

Hoyt Long, Tom McEnaney, and Richard Jean So
Patterns Taken for Wonder is a book project-in-progress.  The manuscript has two main goals.  First, it provides a new history of literary modernism through the lens of computational and data methods from the social sciences, such as machine learning and social network analysis.  For the past three years, we have assembled a large database of over 50,000 modernist poems, thousands of novels, and hundreds of “little magazines” from the United States, England, Latin America, China, and Japan as part of our Global Literary Networks project.  We leverage this corpus to explore new claims about the history of modernism at scale, searching for patterns and structures otherwise invisible to the human eye.  We then combine these interpretations with traditional close reading and historicist methods.
Second, our book is simultaneously a history of the idea of computation and algorithmic reading within modernism itself.  That is, we see literary modernism as anticipating many contemporary ideas about automated text analysis we find in today’s data sciences.  For example, we see this in Marinetti’s interest in language as a mere “system” composed of “atomized” pieces that can be constantly recombined, which resonates with the “bag of words” approach popular in Natural Language Processing.  We also find this in the work of prominent modernist scholars, such as Hugh Kenner, who were drawn to the use of computation to process and find patterns within modernist texts.  In sum, we discern in modernism an important prehistory to our current “big data” moment in which the past can be read forward into the present, and vice versa, the two mutually illuminating.
Our project brings these two strands together to model a new form of literary criticism.  It is a model that attempts to integrate machine and human forms of interpretation, taking seriously the way that a machine understands a text, and putting that into dialogue with conventional human/humanist epistemologies of literature and art.  So far, we have called this method of reading “literary pattern recognition.”  We believe that the intelligent and critical synthesis of machine and human modes of explication can reveal new patterns of meaning both within individual texts, as well as aggregrates of texts at scale.
At the same time, Patterns Taken for Wonder makes a series of sociological and historical claims about literary modernism that exploits the power of big data and computational tools.  We build on this new reading model to reexamine the core categories of modernist criticism, pairing canonical concepts, such as “the author,” with contemporary social scientific categories, such as “agent,” reading each through the other.  The book will consist of five major case studies that work through a variety of different contexts, such as the Harlem Renaissance and stream-of-consciousness, to see how this method plays out in practice and tells us something new about modernism.  Importantly, our case studies respond to the recent transnational turn in modernism studies by working through canonical and non-canonical, Western and non-Western, examples.
The title of our book is a nod to Franco Moretti’s important Signs Taken for Wonder, which explored literary texts as not merely singular examples of expression, but as literary systems that are tokens of greater social and political realities.  This book was important in advancing a modern sociological approach to literary study.  We see our own work as extending this project: to reread the modernist text as in part constituted by and animated by algorithmic patterns of meaning not incommensurable with current machine models of interpretation; and to see texts as not only sociological tokens, but also, as contributing to and in part shaped by vast patterns of culture.  Most broadly, Patterns Taken for Wonder is not a simple “application” of big data methods for literary criticism.  It is an attempt to integrate humanist and scientific approaches to the text in order to model a new form of cultural criticism.  And with this model, we seek to write a new history of modernism, larger and more empirical than previously seen.
Parts of this project are forthcoming in journals.  “Literary Pattern Recognition: Modernism Between Close Reading and Machine Learning” is under review.  “Patterns Taken for Wonder: Computational Approaches to Global Modernism” has been commissioned for a special issue on “Digital Methods” at MLQ.  Please feel free to contact Hoyt Long or Richard Jean So for preprints.  We are always eager for feedback and comments.  We are also seeking a book publisher.  We expect to have at least half of the book written by Spring of 2016 and the complete manuscript done by Spring of 2017.
Interested editors should contact us; we will be happy to share a book proposal.