Text Analysis

Demonstrates using Python to analyze Tweets, showing how to clean and process textual data before then analyzing it.

Describes using sentiment analysis as a highly accurate proxy for plot movement in novels.

Analyzes Martha Ballard’s exhaustive late eighteenth-century diary via topic modeling using MALLET.

An interactive scholarly work that uncovers the history of the Bible in the nineteenth- and early twentieth-century United States. By identifying and studying biblical quotations in American newspapers, the site offers a commentary on how the Bible was used in public life, uncovering trends and patterns that would be invisible to a single scholar’s reading of these documents.

"Mining the Dispatch" explores the dramatic and often traumatic changes as well as the sometimes surprising continuities in the social and political life of Civil War Richmond using topic modeling. It uses as its evidence nearly the full run of the Richmond Daily Dispatch from the eve of Lincoln's election in November 1860 to the evacuation of the city in April 1865.

Examines Shakespeare's influence on Melville using R to compare the writers, taking into account Melville's highlighting and marking up of the Bard's plays.

Uses sentiment analysis to answer the question "Is Modernist poetry darker than Victorian poetry? (Hypothesis: Yes)"

Uses topic modeling to categorize and enable discovery of articles across the entire eighteenth-century run of the Pennsylvania Gazette, which includes approximately eighty-two thousand articles and advertisements from 1728-1800.