Close-Reading the Endnotes for Word-Frequency Signposts & Polyvocal Citations

1. Abstract

This paper describes a machine-assisted bibliographic analysis of the intertextual networks which are housed in an academic text's endnotes. My method is a three step process: first, run a word-count algorithm over the endnotes; next, identify patterns by subjectively grouping high-frequency words into loose clusters; finally, use these high-frequency signposts to perform a symptomatic close-reading of the endnotes. This project falls under Alison Booth's paradigm of "mid-range reading" because it sacrifices both the granular details of close reading and the massive scalability of distant algorithms. The payoff, however, is a versatile methodology through which digital research is consciously co-constructed with a mechanical collaborator.

My test case is Michael Hardt and Antonio Negri's Empire. I not only identify how monovocal scholarship can intertextually reify hegemonic hierarchies, but also how polyvocal citation can produce the opposite effect. I hope to prompt discussions about the intersections of digital scholarship.

Sean A. Yeager (, The Ohio State University, United States of America

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