Session Submission Summary
Share...

Direct link:

Navigating Political Narratives: New Frontiers in Text Analysis, LLMs and NLP

Thu, September 5, 2:00 to 3:30pm, Pennsylvania Convention Center (PCC), 112A

Session Submission Type: Full Paper Panel

Session Description

This APSA panel delves into the innovative intersection of text analysis, Large Language Models (LLMs), Natural Language Processing (NLP), and political science, showcasing recent advancements and applications in understanding political phenomena. This session presents a series of papers that leverage NLP techniques to extract, analyze, and interpret political language, offering novel insights into the ideological underpinnings, populist rhetoric, and democratic commitments of political leaders. Humeyra Biricik of Oxford University applies LLM analysis to predict democratic backsliding from political speeches, while Siyu Liang of UCLA addresses data scarcity in stance detection by focusing on cross-domain transfer learning. Allison Koh of King’s College London investigates the influence of state actors on social media platforms in the wake of policy changes. Patrick Y. Wu of NYU and his team use generative Large Language Models to analyze moralization and othering in social media content. Lastly, Paulina Garcia Corral of Hertie School leverages NLP to extract and synthesize causal arguments from political texts, offering new insights into political narratives. By blending theoretical insights with empirical research, this panel aims to bridge the gap between technical NLP methodologies and practical political science applications.

Sub Unit

Individual Presentations

Chair

Discussants