Patrick J. Burns

Research Associate at Harvard Human Evolutionary Biology | Formerly Quantitative Criticism Lab, ISAW Library | Fordham PhD, Classics | CLTK contributor

Distant Reading Alliteration in Latin Poetry

Word, Space, Time: Digital Perspectives on the Classical World Digital Classical Association, U. Buffalo April 6, 2013

Abstract

A recent study of alliteration (Roper 2001: 1) begins with the premise that “to date, most discussion of alliteration has been made in passing.” This appears to be true in the study of Latin poetry as well, where many comments on the device are presented in either handbook treatments of Latin poetry or in stylistic overviews of individual authors/works. In this paper, I propose to analyze alliteration across large body of Latin poetry using an algorithmic approach. For my dataset, I will use texts of Latin hexameter poetry found in the Perseus Digital Library. The texts will be analyzed using Python, with each line (and group of adjacent lines) scored and ranked for “alliterative strength.” The major issues are raised in Mayrhofer (1989: 121-125) and his article also proposed an algorithmic solution. In the intervening time, however, improvements on a massive scale have taken place in text-processing solutions and speeds, sophistication of visualizations, and the ability to make data publicly available. Accordingly, it seems worthwhile to revisit the topic. The paper will consist of three parts: 1. an overview of a Pythonic workflow for “distant reading” poetic devices such as alliteration, 2. some suggested algorithms used for determining “alliterative strength”, and 3. a brief discussion of the usefulness of an algorithmic approach to studying poetic features. The goal of this project is to reset the foundation for the quantitative study of alliteration in Latin poetry in order to build a platform for getting meaningful, comparable, and repeatable statistics on the device using widely available reference texts.

Code

Sample Python workflow example can be found here.

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