I am a Marie-Curie CareerFit Research Fellow in CeADAR and the School of Computer Science in University College Dublin, Ireland. My project “Natural Language Processing for Understanding and Classifying Regulatory Risk” examines the relationship between linguistic features and regulatory taxonomies in order to understand how legal information is expressed linguistically, and to efficiently distil useful knowledge from regulatory updates and enforcements. The industry partner on the project is Corlytics.
More broadly, my research focuses on applications of natural language processing to questions in digital humanities and social science. Specific interests include computational models of semantic relations between entities, and methods for extracting political concepts and ideological positions from text.
In 2013 I gained my PhD from the School of Computer Science in University College Dublin, on the topic of understanding and predicting lexical expressions of semantic relations between nouns, particularly in non-lexicalised English noun compounds.
From 2012-2015 I was a Research Officer in the Department of Methodology at the London School of Economics and Political Science, where I helped to develop (with Prof. Kenneth Benoit and others) R software for quantitative text analysis for social science. I also worked on general applications of computational text analysis to political science, such as content analysis of twitter data and ideological scaling of speeches and manifestos.
Links to published research and working papers/articles are at the menu above.