Datamining the Enlightenment through Secondary Sources: JSTOR, Dirty Quantification, and the Future of the Lit Review
The traditional lit review tends to focus on a selection of canonical authors and works, along with a sampling of lesser known (often more recent) references. But “the literature” shares with literature a common feature, namely a great unread. Thanks to interfaces such as JSTOR’s “Data for research,” we can now apply some of the methods that scholars have adapted for the distant reading of literary texts to secondary sources. In this presentation, Professor Edelstein take the scholarship on the Enlightenment as a case-study for data-mining the lit review.
Dan Edelstein, professor of French and, by courtesy, of history, works for the most part on eighteenth-century France, with research interests at the crossroads of literature, history, political theory, and digital humanities. His books include The Terror of Natural Right: Republicanism, the Cult of Nature, and the French Revolution (2009) and The Enlightenment: A Genealogy (2010). He is deeply involved with Mapping the Republic of Letters, a large-scale digital humanities project, one of whose primary aims is to map the correspondence networks of major intellectual figures.