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Graduate School of Library and Information Science |
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Expand SEASR Services Explore text-mining as a tool for understanding the humanities.Co-Principal Investigator: John Unsworth See Also: Project Announcement Awarded in the amount of $761,000 by The Andrew W. Mellon Foundation, the grant will fund use cases by participants at four universities: Dan Cohen, from the Center for History and New Media at George Mason University; Ted Underwood, from the English Department at the University of Illinois; Tanya Clement, Associate Director of Digital Cultures and Creativity at the University of Maryland; and Franco Moretti, the Danily C. and Laura Louise Bell Professor of English and Comparative Literature at Stanford University. The new grant comes at a time of increasing interest in text mining as a technique for producing new research insights into the humanities. It will expand on work completed as part of three other Mellon-supported projects:
“As more and more cultural heritage materials are digitized, it becomes increasingly important to explore computational methods for exploring and understanding those materials at ‘library scale’,” said Dean Unsworth, adding “this is not a substitute for traditional modes of reading and argumentation; rather, it is a new way of finding evidence for those readings and arguments—a kind of ‘attention prosthetic.’ ” Goals of the project include sharing research findings through peer-reviewed publications in print and online, as well as the further development of infrastructure for text-mining. Software development will focus on creating or adapting SEASR modules to explore specific research questions from the use cases and on extending work done in MONK to allow researchers to assemble their own collections out of digital repositories. The main emphasis will be on developing, coordinating, and investigating research questions posed by the participating humanities scholars. Examples include exploring questions related to the evolution of literary style in the 19th-centuryAnglophone novel (Moretti), analyzing oral features of Gertrude Stein’s poetry, prose, and plays in both text and audio recordings (Clement), automated topical classification and visualization of historical documents concerning the events of 9/11 (Cohen), and understanding the impetus for changes in diction during the Romantic era (Underwood). |
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