Justin H. Gross

Also published as: Justin Gross


pdf bib
Examining Political Rhetoric with Epistemic Stance Detection
Ankita Gupta | Su Lin Blodgett | Justin Gross | Brendan O’connor
Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS)

Participants in political discourse employ rhetorical strategies—such as hedging, attributions, or denials—to display varying degrees of belief commitments to claims proposed by themselves or others. Traditionally, political scientists have studied these epistemic phenomena through labor-intensive manual content analysis. We propose to help automate such work through epistemic stance prediction, drawn from research in computational semantics, to distinguish at the clausal level what is asserted, denied, or only ambivalently suggested by the author or other mentioned entities (belief holders). We first develop a simple RoBERTa-based model for multi-source stance predictions that outperforms more complex state-of-the-art modeling. Then we demonstrate its novel application to political science by conducting a large-scale analysis of the Mass Market Manifestos corpus of U.S. political opinion books, where we characterize trends in cited belief holders—respected allies and opposed bogeymen—across U.S. political ideologies.


pdf bib
Analyzing Framing through the Casts of Characters in the News
Dallas Card | Justin Gross | Amber Boydstun | Noah A. Smith
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing


pdf bib
The Media Frames Corpus: Annotations of Frames Across Issues
Dallas Card | Amber E. Boydstun | Justin H. Gross | Philip Resnik | Noah A. Smith
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)


pdf bib
Measuring Ideological Proportions in Political Speeches
Yanchuan Sim | Brice D. L. Acree | Justin H. Gross | Noah A. Smith
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing