hansardr: A Software Package in R
Easily access a cleaned version of the c19 Hansard corpus with improved speaker names in the R environment.
Steph Buongiorno, PhD, is a postdoctoral research fellow at Southern Methodist University, Guildhall. Buongiorno engages in transdisciplinary, computational research for the purpose of innovative and holistic problem-solving. Her work involves combining multiple disciplines to generate new knowledge beyond the boundaries of individual fields. At Guildhall, Buongiorno focuses on two main areas of research that aim to address large-scale problems. Her primary area of research uses human computation gaming to develop tools for fighting human trafficking using human-in-the-loop machine learning techniques. The second area of research revolves around the development of an autonomous agent system driven by large language models (LLMs)--a system that can be used to support research, automation, and a multitude of other activities. Visit GitHub Download CV.
Easily access a cleaned version of the c19 Hansard corpus with improved speaker names in the R environment.
An R software package providing functions for extracting grammatical subject-verb-object (SVO) and subject-verb-adjective complement/ adjective modifier (SVA) triples from text. This linguistically improved algorithm has significantly higher precision and recall measures than existing methods.
This paper describes a method of triples extraction, posextract, which has been designed to meet the increasing need for high-accuracy triples outputs for the analysis of text.
An Python software package providing functions for extracting grammatical subject-verb-object (SVO) and subject-verb-adjective complement/ adjective modifier (SVA) triples from text. This linguistically improved algorithm has significantly higher precision and recall measures than existing methods.
An R software package providing functions for Placeholder description
Export an analysis-ready version of the Daily Editions of the U.S. Congressional Records.
This methods book provides a practical introduction to the R programming language for text mining historical records. And more than just a code cookbook, it offers a critical perspective to handling our human history. It is the companion guide to The Dangerous Art of Text Mining by Jo Guldi.