DOI

10.17077/etd.ot2e09a3

Document Type

Dissertation

Date of Degree

Spring 2018

Access Restrictions

Access restricted until 07/03/2020

Degree Name

PhD (Doctor of Philosophy)

Degree In

Classics

First Advisor

Dilley, Paul

First Committee Member

Riggsby, Andrew M.

Second Committee Member

Gibson, Craig A.

Third Committee Member

Bond, Sarah E.

Fourth Committee Member

Greteman, Blaine

Abstract

In a field as old as Classics, it difficult to find truly innovative approaches to literary works that have been studied for millennia, and it only becomes more difficult to find something new to explore in works as fundamental to the field as Marcus Tullius Cicero’s. However, in the burgeoning field of Digital Humanities, new avenues for textual exploration arise even among the over-picked rubble that is the Classical World. Through the use of computer software, we can search through and statistically analyze corpora of massive sizes. This project uses such techniques to perform a mesoanalysis of Cicero’s corpus. Through the use of R and Gephi, I will “read” Cicero’s works from a distance and see a much broader view of his character than I could through a traditional close reading of a few texts.

This mesoanalysis includes a stylometric analysis of Cicero’s entire corpus, a sentiment analysis of his orations, and a network analysis of his letters. The sentiment analysis will explore Cicero as a literary figure. Through a hierarchical cluster analysis in R, I will assess not only how his style changes from genre to genre but within a genre (orations) as well. That analysis will close with an exploration of the lexical richness of his works, how it varies from genre to genre and over his lifetime. For the sentiment analysis, I built a lexicon based on Stoic theory, primarily as it is explained in the Tusculunae Disputationes, and Robert Kaster’s work with emotional scripts. After the lexicon was built, I applied it to Cicero’s orations in a method similar to Matthew Jockers’ syuzhet package for R, and I traced his use of sentiment across the speech. I then compared those trajectories to Latin rhetorical theory, especially the theories included in Cicero’s own treatises, in order to see if Cicero had put into effect his own advice or if he had a few techniques that he kept hidden. The mesoanalysis closes with a network analysis of the Epistulae ad Familiares. I merged Cicero’s social network with a sentiment analysis in order to assess how Cicero felt about and interacted with his peers. From this analysis, one could gather an idea of Cicero as a person. At the end of the mesoanalysis, we can attain a much broader sense of Cicero’s character.

This project also has a second aim, and that is to explain how these techniques could be applied to other literary corpora, outside of Cicero’s and Latin. I have carefully detailed my process and provide more instruction in my appendices so that readers could attempt these analyses and be successful in them.

Keywords

Digital Humanities, Latin, Marcus Tullius Cicero, Network Analysis, Sentiment Analysis, Text Analysis

Pages

xv, 319 pages

Bibliography

Includes bibliographical references (pages 312-319).

Comments

This thesis has been optimized for improved web viewing. If you require the original version, contact the University Archives at the University of Iowa: http://www.lib.uiowa.edu/sc/contact/

Copyright

Copyright © 2018 Caitlin A. Marley

Available for download on Friday, July 03, 2020

Included in

Classics Commons

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