Marti Hearst (UC Berkeley)
December 5, 2013
Talk was not filmed at the speaker’s request.
In this talk I will describe a project whose goal is to help scholars and analysts discover patterns and formulate and test hypotheses about the contents of text collections, midway between what humanities scholars call a traditional “close read” and the new “distant read” or “culturomics” approach. To this end, we describe a text analysis and discovery tool called WordSeer that allows for highly flexible “slicing and dicing” (hence “sliding”) across a text collection. We illustrate the text sliding capabilities of the tool with two real-world case studies from the humanities and social sciences – the practice of literacy education, and U.S. perceptions of China and Japan over the last 30 years – showing how the tool has enabled scholars with no technical background to make new discoveries in these text collections. (Joint work with Aditi Muralidharan. Sponsored by NEH HK-50011.)
Dr. Marti Hearst is a professor in the School of Information at UC Berkeley, with an affiliate appointment in the Computer Science Division. Her primary research interests are user interfaces for search engines, information visualization, natural language processing, and empirical analysis of social media. She has recently completed the first book on Search User Interfaces. Prof. Hearst received her BA, MS, and PhD degrees in Computer Science from the University of California at Berkeley, and she was a Member of the Research Staff at Xerox PARC from 1994 to 1997. Prof. Hearst has served on the Advisory Council of NSF’s CISE Directorate and was co-chair of the Web Board for CACM. She is a member of the Usage Panel for the American Heritage Dictionary and is on the Edge.org panel of experts. Prof. Hearst is on the editorial boards of ACM Transactions on the Web and ACM Transactions on Computer-Human Interaction and was formerly on the boards of Computational Linguistics, ACM Transactions on Information Systems, and IEEE Intelligent Systems. Prof. Hearst has received an NSF CAREER award, an IBM Faculty Award, a Google Research Award, an Okawa Foundation Research Grant, and two Excellence in Teaching Awards.