Classical Intertextuality and Computation

FAIN: HD-248410-16

University of Texas, Austin (Austin, TX 78712-0100)
Pramit Chaudhuri (Project Director: September 2015 to March 2021)

A research project on how techniques originally developed for computational biology, such as sequence alignment, can illuminate influences and stylistic attributes among classical Latin and Greek texts.

Literary scholarship has long been preoccupied with identifying verbal and stylistic relations among texts (“intertextuality”). This project is a collaboration between literary critics, systems biologists, and computer scientists to develop new computational tools for the study of such intertextual relations. These tools will enable researchers to trace connections among Latin and Greek texts at much a higher order of scale and efficiency than manual searches: 1) a sequence alignment tool, inspired by a core technique in genomics, which identifies verbal parallels that are close but inexact (the commonest kind of intertextuality); 2) a digital Greek-Latin thesaurus to enable identification of parallels across languages by meaning; 3) a set of tools for classification of texts according to various stylistic metrics, especially useful for studies of quotation and attribution; 4) phylogenetic methods to chart the evolutionary histories of classical texts and their traditions of reception.

Media Coverage

New Approach Developed by Humanists and Scientists Maps Evolution of Literature (Media Coverage)
Publication: UT News
Date: 4/10/2017
URL: https://news.utexas.edu/2017/04/05/mapping-the-evolution-of-literature-using-science-techniques

Associated Products

Quantitative criticism of literary relationships (Article)
Title: Quantitative criticism of literary relationships
Author: Joseph Dexter
Author: Theodore Katz
Author: Nilesh Tripuraneni
Author: Tathagata Dasgupta
Author: Ajay Kannan
Author: James A. Brofos
Author: Jorge A. Bonilla Lopez
Author: Lea A. Schroeder
Author: Adriana Casarez
Author: Maxim Rabinovich
Author: Ayelet Haimson Lushkov
Author: Pramit Chaudhuri
Abstract: Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships (“intertextuality”) and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term “quantitative criticism,” focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca’s main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions
Year: 2017
Primary URL: http://www.pnas.org/content/early/2017/03/28/1611910114.full
Access Model: Open Access
Format: Journal
Periodical Title: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences of the United States of America

Bioinformatics and Classical Literary Study (Article)
Title: Bioinformatics and Classical Literary Study
Author: Pramit Chaudhuri
Author: Joseph Dexter
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.
Year: 2017
Primary URL: https://jdmdh.episciences.org/paper/view?id=3807
Access Model: Open Access
Format: Journal
Periodical Title: Journal of Data Mining and Digital Humanities

Quantitative Criticism Lab (Web Resource)
Title: Quantitative Criticism Lab
Author: Pramit Chaudhuri
Abstract: Founded in 2014 by a team of humanists, biologists, and computer scientists, the Quantitative Criticism Lab explores new approaches to the study of literature and culture. Taking inspiration from a wide range of quantitative disciplines - machinelearning, natural language processing, bioinformatics, and systems biology - we seek to integrate literary criticism, philology, and big data. We have a particular interest in the literature of ancient Greece and Rome and the profound influence ofthe Classics on later traditions.
Year: 2017
Primary URL: https://www.qcrit.org/

Phylogenetic Profiling and the Reception of Classical Drama (Conference Paper/Presentation)
Title: Phylogenetic Profiling and the Reception of Classical Drama
Author: Ariane Schwartz
Author: Joseph Dexter
Author: Pramit Chaudhuri
Abstract: Recent developments in reception studies, world literature, and the digital humanities have made effective use of enlarged scale in posing and answering new research questions. The continuously expanding database of the Archive of Performances of Greek and Roman Drama (APGRD; represented in Macintosh et al. 2005), the encompassing of substantial non-western material in comparative literary studies (Damrosch 2003), and the inclusion of vast quantities of non-canonical works enabled by text digitisation (Moretti 2009, Barker and Terras 2016, Long and So 2016) collectively entail new forms of data gathering and visual presentation, which in turn open new hermeneutic horizons. This paper draws inspiration from computational biology to offer a new method of organising, visualising, and interpreting the reception histories of literary works, focusing on classical drama. We repurpose a technique known as phylogenetic profiling to chart the evolution of Plautus’ Amphitryon through a sample of 22 adaptations ranging from the Middle Ages to the 20th century. The paper describes the new methodology, presents resulting analyses about the treatment of dramatic characters across the tradition, and discusses implications for the practice of classical reception studies. To demonstrate the scalability of the approach, we conclude by briefly describing a similar profile of Sophocles’ Antigone, which incorporates 129 adaptations spanning four continents.
Date: 1/7/2017
Primary URL: https://classicalstudies.org/annual-meeting/148/abstract/phylogenetic-profiling-and-reception-classical-drama
Conference Name: 2017 Society for Classical Studies Annual Meeting

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