Abstract
This paper describes the Quantitative Criticism Lab, a collaborative initiative between classicists, quantitative biologists, and computer scientists to apply ideas and methods drawn from the sciences to the study of literature. A core goal of the project is the use of computational biology, natural language processing, and machine learning techniques to investigate authorial style, intertextuality, and related phenomena of literary significance. As a case study in our approach, here we review the use of sequence alignment, a common technique in genomics and computational linguistics, to detect intertextuality in Latin literature. Sequence alignment is distinguished by its ability to find inexact verbal similarities, which makes it ideal for identifying phonetic echoes in large corpora of Latin texts. Although especially suited to Latin, sequence alignment in principle can be extended to many other languages.
Highlights
The Quantitative Criticism Lab (QCL; www.qcrit.org), directed by the co-authors, grew out of shared interests in classical intertextuality dating back to a seminar taught in 2009
The main object of the presentation is to describe a tool we have developed for intertextuality detection that exploits a technique from computational biology and linguistics known as sequence alignment
After a brief contextualization of the approach in relation to other computational studies of culture, we explain the methodology of sequence alignment, and discuss case studies in its initial application to intertextuality in Latin epic poetry and tragedy
Summary
The Quantitative Criticism Lab (QCL; www.qcrit.org), directed by the co-authors, grew out of shared interests in classical intertextuality dating back to a seminar taught in 2009. QCL has used stylometry and machine learning to obtain nuanced portraits of the cultural evolution of literature, focusing especially on two richly imitative strands of the Latin literary tradition - pseudo-Senecan and Senecan influenced tragedy, and citations of earlier fragmentary historians in Livy’s monumental history of Rome (Dexter et al, 2017). Diverse in their humanistic aims, these applications of biology tend to mirror one of two principal approaches that have long been characteristic of literary study, historicism and formalism. After a brief contextualization of the approach in relation to other computational studies of culture, we explain the methodology of sequence alignment, and discuss case studies in its initial application to intertextuality in Latin epic poetry and tragedy
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