Queens of Antiquity

Project Summary

Understanding how to generate, analyze, and work with datasets in the humanities is often a difficult task without learning how to code or program. In humanities centered courses, we often privilege close reading or qualitative analysis over other methods of knowing, but by learning some new quantitative techniques we better prepare the students to tackle new forms of reading. This class will work with the data from the HathiTrust to develop ideas for thinking about how large groups and different discourse communities thought of queens of antiquity like Cleopatra and Dido.

Please refer to https://sites.duke.edu/queensofantiquity/ for more information.

Themes and Categories
Year
2018

Graduate Student: Grant Glass

Faculty: Dr. Charlotte Sussman

Course: “Queens of Antiquity” (English 390S-7; Spring 2018)

Grant Glass taught this Data Expedition activity to students in ENGL 290, a spring 2019 course aimed at undergraduates. This experience exemplified that by introducing simple “distant reading” or qualitative concepts in a humanities undergraduate classroom, students would be able to use these tools to drive new types of research questions and think about how reading can include qualitative analysis.

The goals were to give students an introduction to “distant reading,” show how data and collections are created, what algorithms we can apply to those collections, and what types of analysis we can do from the results.

Over the course of two, 1.5-hour class sessions, 10 undergraduates were given the opportunity to create their own datasets and explore the results. For the end product, students created posts to discuss how the visualizations created from their collections helped them better understand.

Guiding Questions

  • What visualization is the most useful? Why?
  • What does the visualization help you understand about the corpus? What does it obscure?
  • What research questions can you generate from the visualization?

The Dataset

Dido

Elizabeth 1

Anne

Cleopatra

In-Class Exercises

Creating Collections with Hathitrust

Understanding the Visualizations

Related People

Related Projects

In this two-day, virtual data expedition project, students were introduced to the APIM in the context of stress proliferation, linked lives, the spousal relationship, and mental and physical health outcomes.

Stress proliferation is a concept within the stress process paradigm that explains how one person’s stressors can influence others (Thoits 2010). Combining this with the life course principle of linked lives explains that because people are embedded in social networks, stress not only can impact the individual but can also proliferate to people close to them (Elder Jr, Shanahan and Jennings 2015). For example, one spouse’s chronic health condition may lead to stress-provoking strain in the marital relationship, eventually spilling over to affect the other spouse’s mental health. Additionally, because partners share an environment, experiences, and resources (e.g., money and information), as well as exert social control over each other, they can monitor and influence each other’s health and health behaviors. This often leads to health concordance within couples; in other words, because individuals within the couple influence each other’s health and well-being, their health tends to become more similar or more alike (Kiecolt-Glaser and Wilson 2017, Polenick, Renn and Birditt 2018). Thus, a spouse’s current health condition may influence their partner’s future health and spouses may contemporaneously exhibit similar health conditions or behaviors.

However, how spouses influence each other may be patterned by the gender of the spouse with the health condition or exhibiting the health behaviors. Recent evidence suggests that a wife’s health condition may have little influence on her husband’s future health conditions, but that a husband’s health condition will most likely influence his wife’s future health (Kiecolt-Glaser and Wilson 2017).

Annie Xu (Rice, CEE), Liuren Yin (ECE), and Zoe Zhu (Data Science) spent ten weeks analysing usage data for MorphoSource, a publicly available 3D data repository maintained by Duke University. Working with Python and Tableau, the team developed an interactive dashboard that allows MorphoSource staff to explore usage patterns for site visitors who view 3D files representing objects from primate skulls to historical art pieces.

 

View the team's project poster here

Watch the team's final presentation on Zoom here:

 

Project Leads: Doug Boyer, Julia Winchester

After London was destroyed during the Great Fire of 1666, it was reconstructed into the “emerald gem of Europe,” a utopian epicenter focused on England’s political and economic interests. For whom was the utopia constructed? Who determined its architectural choices? And what did such a utopia look like in seventeenth-century London?


Our research uses Natural Language Processing to analyze semantic trends in digitized text from the online database “Early English Books Online” (EEBO-TCP https://textcreationpartnership.org/tcp-texts/eebo-tcp-early-english-books-online/) to answer such questions. After applying methods such as word-embedding, sentiment analysis, and hapax richness, we provide an overview of themes in the seventeenth century; specifically, we conducted case studies on changes to coal taxes within the period and the reconstruction of St Paul's Cathedral. Our results thus show that, while a utopian society was originally intended to be built for the people, the project’s motivation eventually shifted to a political purpose, as evidenced by the approval of more costly city projects. In response to backlash against the increase of taxes on coal to support large-scale building projects, the ruling class highlighted positive outcomes in printed materials in order to convince working class persons that their collected taxes contributed to a greater good, despite evidence to the contrary. Finally, during key historical events, sentiment and hapax richness are shown to have an inverse relationship, the results of which can demonstrate how London writers engaged with text and genre as forms of protest.

View the team's project poster here

Watch the team's final project presentation on Zoom: