Adapting Public Personas: A Multimodal Study of U.S. Legislators' Cross-Platform Social Media Strategies

Abstract: Current cross-platform social media analyses primarily focus on the textual features of posts, often lacking multimodal analysis due to past technical limitations. This study addresses this gap by examining how U.S. legislators in the 118th Congress strategically use social media platforms to adapt their public personas by emphasizing different topics and stances. Leveraging the Large Multimodal Models (LMMs) for fine-grained text and image analysis, we examine 540 legislators personal website and social media, including Facebook, X (Twitter), TikTok. We find that legislators tailor their topics and stances to project distinct public personas on different platforms. Democrats tend to prioritize TikTok, which has a younger user base, while Republicans are more likely to express stronger stances on established platforms such as Facebook and X (Twitter), which offer broader audience reach. Topic analysis reveals alignment with constituents' key concerns, while stances and polarization vary by platform and topic. Large-scale image analysis shows Republicans employing more formal visuals to project authority, whereas Democrats favor campaign-oriented imagery. These findings highlight the potential interplay between platform features, audience demographics, and partisan goals in shaping political communication. By providing insights into multimodal strategies, this study contributes to understanding the role of social media in modern political discourse and communications.