The millions of digitized historic newspaper pages within Chronicling America, a joint initiative between the Library of Congress and the National Endowment for the Humanities, represent an incredibly rich resource for a broad range of users. Historians, journalists, genealogists, students, and members of the American public explore the collection regularly via keyword search.
But how do we navigate the abundant visual content? In this talk, I will present my project, Newspaper Navigator, which I created as an Innovator in Residence at the Library of Congress in collaboration with LC Labs, the National Digital Newspaper Program, and IT Design & Development, as well as Professor Daniel Weld at the University of Washington. In particular, I will discuss three components of the project:
- Extracting visual content from 16+ million pages in Chronicling America using machine learning, resulting in the Newspaper Navigator dataset.
- Re-imagining how we search over the extracted visual content using the Newspaper Navigator search application.
- Critically examining the Newspaper Navigator dataset and machine learning techniques employed, as described in the project’s data archaeology.
In this presentation, I will also discuss how Newspaper Navigator contributes to research in a range of disciplines, from machine learning and human-computer interaction to the digital humanities and history.
- Newspaper Navigator dataset: https://news-navigator.labs.loc.gov/
- Newspaper Navigator search application: https://news-navigator.labs.loc.gov/search
- Newspaper Navigator data archaeology: http://www.digitalhumanities.org/dhq/vol/15/4/000578/000578.html
- Newspaper Navigator project description & other links: https://bcglee.github.io/newspaper-navigator.html
digitalhistory: Benjamin Lee: Newspaper Navigator: Reimagining Digitized Newspapers with Machine Learning, in: Digital History Berlin (Blog), erschienen am: 16. Januar 2023, Internet: https://dhistory.hypotheses.org/3286.