Jeffrey Binder / English

Graduate Student Researcher
Started at the NML: February 2014

Projects: Reading with Emotion in the Eighteenth Century; The Distance Machine

Jeffrey Binder

Jeffrey Binder is a PhD student in English at CUNY who specializes in nineteenth century American literature, digital humanities, and critical theory.  Jeff comes to the humanities from a background in computer programming, and much of his work involves putting new digital technologies into dialogue with their historical precedents.  He is especially interested in the explosion in the nineteenth century of highly-structured textual forms such as indexes, tables, mathematical notations, and paperwork that are both directly connected to the development of computers and deeply integrated into the structures of modern political and business institutions.  He also works on the relationship of rhetoric and literary style to American conceptions of public space, and on the ways American authors (especially Melville) have negotiated the tension between individual belief and the conventional nature of language.

With Collin Jennings, a PhD candidate in English at NYU, Jeff developed the Networked Corpus, which provides a new way of navigating texts using the statistical method known as topic modeling.  Based on this software, Jeff and Collin created an environment that allows the detailed comparison of a topic model with the subject index from the 1784 edition of Adam Smith’s The Wealth of Nations.  They found that these two technologies, despite their superficial similarities, represent the contents of a text in radically different ways.  Jeff and Collin presented on this project at MLA 2014, and are currently preparing a paper on the topic for publication.

At the New Media Lab, Jeff is working on a Web site about the ways early American lexicographers and writers dealt with the divergence of British and American dialects of English.  The site will include both an archive of annotated primary sources and interactive visualizations based on data about word usage over time on both sides of the Atlantic.  This project will bring together two different technologies that address changes in language: the nineteenth-century dictionary, which attempted to impose an artificial regularity on people’s vocabulary, and modern methods of corpus analysis, which aims to give a rough sense of when words come into or go out of common use in print.