2025/04/23 by Lukas Birkenmaier, Clemens M. Lechner · 1 voice
Social Sciences · #Computational and Text Analysis Methods
paper · pdf · doi:10.31219/osf.io/7nhjz_v1
Citizens’ opinions about politicians are shaped by their perceptions of politi-cians’ personalities, characters, and traits. Whereas prior research has investigated the traits voters value in politicians, less attention has been given to how politicians project these traits in their public communication. This may stem from challenges in defining and measuring politicians’ personality traits at scale. To address this challenge, we propose a novel computational approach to measure politicians’ personalities from public statements. First, we develop a conceptual model that links a politician’s intrinsic and public personality using public statements, which we term personality cues. Second, we operationalize two key political traits—agency and communion—using a theory-driven, domain-specific framework. We then compare various computational text analysis methods for extracting these traits from a large corpus of politicians’ parliamentary speeches, social media posts, and interviews. We validate our approach using a comprehensive set of human-labeled data, functional tests, and analyses of how prominently personality traits appear in the statements of German politicians and in the 2024 U.S. presidential debate between Donald Trump and Kamala Harris. Our findings indicate that prompting-based techniques, particularly those leveraging advanced models such as DeepSeek-V3, outperform supervised and semi-supervised methods. These results point to promising directions for advancing political psychology.