Advanced Collaborative Support (ACS) is a scholarly service at the HTRC offering collaboration between external scholars and HTRC staff to solve challenging problems related to HTRC tools and services. By working together with scholars, we facilitate computational access to HathiTrust Research Center digital tools (HTRC) as well as the HathiTrust Digital Library (HTDL) based on individual scholarly need. ACS will drive innovation at the scholar's digital workbench for enhancing and developing new techniques for use within the HTRC platform. For questions, please send an email to firstname.lastname@example.org.
Computational Support for Reading Chicago Reading
Robin Burke, John Shanahan, Ana Lucic, DePaul University
The Reading Chicago Reading team will seek to extend their own research on the “One Book, One Chicago” city-wide reading program by incorporating textual analysis on books chosen for the OBOC program, as well as comparison texts. Further, the resulting textual analysis—including toponym extraction, sentiment analysis, and story arc detection—will be paired with library patron, circulation and demographic data to present a fuller picture about the OBOC program, and the books chosen for inclusion.
Modeling the History of Book Design
David Bamman and Bjorn Hartmann, University of California, Berkeley
This project will utilize the HTRC Data Capsule to conduct feature extraction on page images from 10,000 in-copyright books in the HathiTrust repository, extracting features such as page construction, line justification, leading between baselines, kerning between letter pairs/combinations, line density per page, characters per line, position of images, typeface (serif, sans-serif) and font size. Beyond the analysis and utility of the extracted feature set, this project also seeks to serve as a use case for engagement with HathiTrust/HTRC beyond books-as-strings-of-words analysis.
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