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DH Event on campus Speaker Series

DH Event: Digital Humanities, Data Analysis and Its Possibilities

Visiting us from University of Richmond, Assistant Professors Lauren Tilton and Taylor Arnold will give a talk on exploratory data analysis methods, which have received limited visibility in DH. In this talk, they will give an overview of the historical developments of exploratory data analysis and statistical computing. They will show, through examples from their work on visual culture, how both have the potential to shape digital humanities projects and pedagogy.

Thursday, February 2nd, 2017
12:15-1:15
IQ Center (Science Addition 202A)
Please register



Lauren Tilton is Visiting Assistant Professor of Digital Humanities at the University of Richmond and member of Richmond’s Digital Scholarship Lab. Her current book project focuses on participatory media in the 1960s and 1970s. She is the Co-PI of the project Participatory Media, which interactively engages with and presents participatory community media from the 1960s and 1970s. She is also a director of Photogrammar, a web-based platform for organizing, searching and visualizing the 170,000 photographs from 1935 to 1945 created by the United States Farm Security Administration and Office of War Information (FSA-OWI). She is the co-author of Humanities Data in R (Springer, 2015). She is co-chair of the American Studies Association’s Digital Humanities Caucus.


Taylor Arnold is Assistant Professor of Statistics at the University of Richmond. A recipient of grants from the NEH and ACLS, Arnold’s research focuses on computational statistics, text analysis, image processing, and applications within the humanities. His first book Humanities Data in R, co-authored with Lauren Tilton, explores four core analytical areas applicable to data analysis in the humanities: networks, text, geospatial data, and images. His second book, the forthcoming A Computational Approach to Statistical Learning (CRC Press 2018), explores connections between modern machine learning techniques with connections in statistical estimation. Numerous journal articles extrapolate on these ideas in the context of particular applications. Arnold has also released several open-source libraries in R, Python, Javascript and C. Visiting appointments have included Invited Professor at Université Paris Diderot and Senior Scientist at AT&T Labs.

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