The Power of Place: Structure, Culture, and Continuities in U.S. Women’s Movements
Laura Nelson, Northeastern University
Dr. Nelson’s project will study the women's movement in the United States from 1848-1975 in two cities, New York City and Chicago, using new advances in network analysis and computational text analysis to identify structural and cultural diversity. This approach is three-pronged: building a workset of writing by individuals and organizations within the movements in New York and Chicago, using network analysis to measure the structure of this movement, and conducting computational text analysis to measure the underlying culture and ideas within the movement, including lexical analyses to identify distinctive words and topic modeling to identify dominant themes.
A Computational History of the U.S. Novel, 1950-2000
Richard Jean So, McGill University
Dr. So’s project seeks to write a new history of the American novel by examining a series of large textual datasets focused on the full cycle of the U.S. literary field from production to reception to canonization. The major goal is to identify the emergence of new patterns of language, style, discourse and themes in American novels as they appear at different moments in the cycle of literary production and reception, including publication via large publishing houses such as Random House, and book reviews in major U.S. periodicals. This will be achieved through using the HTRC Data Capsule environment to undertake text analysis of full texts, including using various methods in Machine Learning and Natural Language Processing, such as topic models, word embeddings, and specialized tools such as BookNLP, which allows for the extraction of grammatical dependencies and characters.
Measuring Literary Novelty
Laura McGrath, Devin Higgins, Arend Hintze, Michigan State University
This work draws on ongoing collaborative efforts to develop a method for applying genetic sequencing tools to the study of literature in order to identify and measure literary novelty, and address questions of literary history, canonicity, and prestige. Previous results have been suggestive of a prominent connection between the purely information-based novelty of the sequences of characters that comprise literary texts, and the experimental newness we associate with modernist literary texts. Leveraging the HTRC Data Capsule will offer the potential to apply this theory at scale for the first time, and potentially lead into new research into modernism and the literary history of the 20th century.
A Writer’s Workshop Workset with the Program Era Project (PEP)
Nicholas Kelly, Loren Glass, Nikki White, University of Iowa
The PEP team will compile a proof-of-concept workset with, at first, prominent individuals (faculty, staff, students) who were involved with the Iowa Writers’ Workshop (IWW), then produce “style cards” for each author’s works (by volume), based on stylometric data gathered through text analysis of the IWW workset within the HTRC Data Capsule. It is the goal of the project to also create a living workset that can be continually updated for scholars who wish to engage with IWW authors and their writing.
The Life of Words
David-Antoine Williams, The University of Waterloo
This project aimed to match Oxford English Dictionary (OED) references to HathiTrust volume IDs, in order then to draw down associated metadata using the heterogenous and fragmented bibliographical data in OED2 and OED3. It furthered the work of The of The Life of Words (LOW), a research project in its third year, led by Dr. Williams at St Jerome’s University in the University of Waterloo in Canada. The aim of the project is to enhance the OED with metadata concerning its corpus of 3.5 million quotations.
Fighting Fever in the Caribbean: Medicine and Empire, 1650-1902
Project report: The Chicago School: Evolving Systems of Value
Signal and Noise and Pride and Prejudice: Toward an Information History of Romantic Fiction
Project report: Signal and Noise and Pride and Prejudice
The Trace of Theory
Rockwell, Mandell, Sinclair, Wilkens, and Brown aim to subset theoretical subsets from the HT public corpus and apply large-scale topic modeling on the subsets. The researchers will develop tools and computational methods for tracking the concept of "theory”.
Project report: The Trace of Theory project