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Modalities of Textual Analysis: Exploring British Periodicals


Jan Kim

Marco Georgaklis

Adrian Wong



About the Project

How can you identify and explore patterns across millions of documents? In this fellowship, Buchanan Library Fellows learned state-of-the-art techniques for text mining at scale. Fellows joined an ongoing research project to analyze constellations of information in ProQuest's British Periodicals Collections. Depending on interest, Fellows learned to use Databricks, a framework for analyzing datasets on Spark; Rumble, a query engine for exploring semi-structured documents on Spark; and Netsblox, a block-based programming language with robust connections to network-based tools like Stanford’s CoreNLP. They learned how to extract information from big data sets in the humanities, social sciences, or other fields with relative ease and confidence. 

The Fellows

Roman Brasoveanu, Jingyi Chen, Marco Georgaklis, Jan Kim, Suiyang Mai, Ludwig Noya, Kwan Nok,  Adrian Wong

The Instructors

Cliff Anderson, Associate University Librarian for Research and Digital Strategy, Interim Director of the VRC

Mark Schoenfield