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Products for grant HD-248410-16

HD-248410-16
Classical Intertextuality and Computation
Pramit Chaudhuri, University of Texas, Austin

Grant details: https://securegrants.neh.gov/publicquery/main.aspx?f=1&gn=HD-248410-16

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


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