Pattern Recognition through Computational Stylistics: Old English and Beyond

FAIN: HD-50300-08

Wheaton College (Norton, MA 02766-2322)
Mark David LeBlanc (Project Director: October 2007 to November 2010)

Development of a prototypical suite of computational tools and statistical analyses to explore the corpus of Old English literature using the genomic approach of tracing information-rich patterns of letters as well as that of literary analysis and interpretation.

Professors Drout, Kahn, and LeBlanc have prepared a Level II proposal to prototype a suite of computational tools and statistical analyses to explore the Old English corpus. This work will serve as a proof of concept for the larger deployment of corpus-independent tools. Anticipated outcomes include scalable, open-source software to facilitate the computation and organization of word frequencies and other patterns and empirical measures of success when using various statistical analyses on the condensed data. An additional and essential outcome from our perspective is how this research leads to and impacts the development of interdisciplinary course materials for our connected (interdisciplinary) undergraduate courses in English, Statistics, and Computer Science in order that computational analyses become a more inviting option for faculty and advanced research students in the Humanities.

Associated Products

Lexos (Computer Program)
Title: Lexos
Author: Mark D. LeBlanc
Abstract: The rapid digitization of texts presents both new opportunities and real barriers of entry to computer-assisted explorations of texts. The Lexos software developed by the Lexomics Project provides a simple, web-based workflow for text processing, statistical analysis, and visualization designed to address these barriers. The project supports Lexos’ core strength as an entry-level tool while seeking to position it as an innovative intervention in Digital Humanities conversations about the interplay of machine learning and text analysis.
Year: 2012
Primary URL: http://lexos.wheatoncollege.edu
Primary URL Description: A simple, web-based workflow for text processing, statistical analysis, and visualization.
Access Model: open access
Programming Language/Platform: Python
Source Available?: Yes

Computer Science for the Rest of Us (Article)
Title: Computer Science for the Rest of Us
Author: RANDALL STROSS
Abstract: Many professors of computer science say college graduates in every major should understand software fundamentals. They don’t argue that everyone needs to be a skilled programmer. Rather, they seek to teach “computational thinking” — the general concepts programming languages employ. The New York Times, Digital Business Day, Digital Domain MARCH 31, 2012
Year: 2012
Primary URL: http://www.nytimes.com/2012/04/01/business/computer-science-for-non-majors-takes-many-forms.html?_r=3&ref=business
Access Model: open, online section of the New York Times
Format: Newspaper

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