Article summary
This study asks whether politicians’ “public personality” traits—specifically agency and communion—can be measured at scale from their public statements using computational text analysis. The authors propose a theory-driven, domain-specific operationalization of agency and communion and compare multiple computational approaches to extract these traits from a large corpus that includes parliamentary speeches, social media posts, and interviews. They validate their approach with human-labeled data, functional tests, and targeted analyses of German politicians and the 2024 U.S. presidential debate featuring Donald Trump and Kamala Harris. The paper reports that prompting-based techniques, especially with advanced models like DeepSeek-V3, performed better than supervised and semisupervised alternatives, while noting this is a multimethod feasibility study rather than a definitive measurement standard.