Working with Text Data and Language Ideologies Online

Working with Text Data: Automatically Extracting Poetry from Scanned Books

John Foley, Assistant Professor in Computer Science

Foley studies computational methods for understanding and organizing noisy text data. In this lightning talk, he will introduce his research area, discuss how poetry was collected from digitally scanned books, and talk about some ongoing work in understanding allusion in literary texts. The poetry project and dataset live at: https://poetry.jjfoley.me/

Language Ideologies and How People Perceive Them Online

Gyula Zsombok, French and Francophone Studies

This talk will present some research directions and methodologies focusing on the representation of language ideologies online and how language users perceive these ideologies. The area of study is French, considered one of the most regulated European languages that is supervised by the Académie française and the Office québecois de la langue française. While these institutions possess significant power over linguistic standards, often supported by legislation in France and Québec, the question remains whether speakers actually comply with these standards, and how/what they think about them. This research emphasizes lexical innovations (borrowings, new words, internal creations) and gender-inclusive language (neutral forms, pronouns), with textual sources such as social media data, web page scraping, newspaper articles that are processed and analyzed via statistical and topic models. The goal of this talk is to demonstrate accessible tools that could be used for a variety of research topics in the digital humanities.