Computational Humanities Projects
How do elites maintain power when the world around them is being radically transformed? Between the late sixteenth and early eighteenth centuries, England was reshaped by the explosive growth of global trade. Political and socio-economic elites had to adapt—or risk losing power. Who benefited from these changes, who lost out,...
A team of students led by researchers in English and Computer Science will investigate a fundamental question about artificial intelligence: can machines be truly creative? Students will design experiments comparing human and AI storytelling, build datasets and computational tools to measure originality and surprise, and explore what current language models...
Is it ethically permissible to sell, buy, and use luxury goods? What labor practices do we tolerate to make these goods available? In the late Middle Ages and Renaissance, England was faced with an ever-growing supply of new and exciting goods, made possible by new trade routes to the New...
A team of students will collaborate with a doctoral fellow in Computational Humanities and the Asian American Studies Librarian to develop a statistics-based Natural Language Processing toolkit to study the linguistic styles of Asian American short stories published between 1974 and 2024. This toolkit will support historians, literary scholars, and...
Is it ethically permissible to sell, buy, and use luxury goods? What labor practices do we tolerate to make these goods available? This project traces the early history of these questions as European powers started to exploit the natural resources and peoples of the New World. We want to trace...
Using digitized card catalogs from the David M. Rubenstein Rare Book and Manuscript Library, a team of students explored extracting structured data from over 115,000 subject cards to develop searchable and sortable descriptions of manuscript and archival collections. They prepared the digitized subject cards for online access in the Internet...
A team of students led by a data scientist at NetApp developed the means to evaluate technical documentation through machine learning techniques. Students identified features of language and documents that can be used to demonstrate how effective that documentation is at communicating technical specifications. Additionally, students applied machine learning methods...
Is it ethically permissible to sell, buy, and use luxury goods? What labor practices do we tolerate to make these goods available? In the late Middle Ages and Renaissance, England was faced with an ever-growing supply of new and exciting goods, made possible by new trade routes to the New...
A team of students led by an interdisciplinary group of faculty at the intersection of policy, economics, and computer science used statistical and machine learning methods to assess and map the discourse of speeches (1919-2022) by applied economists on food and agricultural policy. Understanding the historical underpinnings of these policies...
A team of students led by professors Maurizio Forte, Classical Studies and AAHVS and Leonard White, Neurology, studied the embodied aesthetic experience engendered by real and virtual interactions with archeological ruins (“ruinscapes”) and virtual representations of places, spaces, and cultural artifacts associated with an ancient city. The focus will be...
The students in this project worked on a pervasive question in literary, film, and copyright studies: how do we know when a new work of fiction borrows from an older one? Many times, works are appropriated, rather than straightforwardly adapted, which makes it difficult for human readers to trace. As...
How Much Profit is Too Much Profit? Chris Esposito (Economics), Ruoyu Wu (Computer Science), and Sean Yoon (Masters, Decision Sciences) spent ten weeks building tools to investigate the historical trends of price gouging and excess profits taxes in the United States of America from 1900 to the present. The team used a variety of text-mining...
The aim of this project was to explore how U.S. mass media—particularly newspapers—enlists text and imagery to portray human rights, genocide, and crimes against humanity from World War II until the present. From the Holocaust to Cambodia, from Rwanda to Myanmar, such representation has political consequences. Coined by Raphael Lemkin,...
The Middle Passage, the route by which most enslaved persons were brought across the Atlantic to North America, is a critical locus of modern history—yet it has been notoriously difficult to document or memorialize. The ultimate aim of this project is to employ the resources of digital mapping technologies as...
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...
This two-week teaching module in an introductory-level undergraduate course invites students to explore the power of Twitter in shaping public discourse. The project supplements the close-reading methods that are central to the humanities with large-scale social media analysis. This exercise challenges students to consider how applying visualization techniques to a...
This Data Expedition introduces students to network tools and approaches and invites students to consider the relationship(s) between social networks and social imaginaries. Using foundation-funding data that was collected from the The Foundation Directory Online, the Data Expedition enables students to visualize and explore the relationship between networks, social imaginaries, and...
Led by Dr. Eva Wheeler, this project considers how racial language in African American literature and film is rendered for international audiences and traces the spread of these translations. To address the study’s primary questions, the team analyzed a preliminary dataset and explored the relationship between translation strategy and different...
We apply word embedding models to corpora from the start of the Early Modern period, when the market economy began to dramatically expand in England. Word embedding models use neural networks to map vectors to words so that semantic relationships are preserved within the vectors’ geometry. Such models have been...
The visibility of hate groups such as the Alt-Right became mainstream into contemporary political culture during the Unite the Right Rally in Charlottesville, VA in 2017. This project aims to explore methods to quantify the presence of Latinxs within the Alt-Right, particularly in how they racialize themselves in a space...
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