This work presents a novel observational study of US congresspeople’s link-based news-sharing behaviors and ideological presentations across Facebook and Twitter. By analyzing the web domains these politicians share, we estimate their political ideologies and measure ideological extremity across the political and social contexts of these platforms. Our findings show that these politicians present as more ideologically extreme on Facebook than they appear on Twitter, particularly among Democrats. However, this difference is relatively small compared to the ideological shift between a politician’s publicly funded official account and their campaign account—a shift that is roughly seven times larger. Finally, we observe that these changes are not uniform over time across parties; expressed polarization within the Democratic Party notably increased from 2013 to 2017 before stabilizing, while the Republican Party became markedly more polarized starting in 2020. While more research is needed to identify the specific affordances that contribute to more expressed polarization on Facebook and potential temporal dynamics between these platforms, this work highlights the limitations of studies that focus on single platforms and opens new avenues for future research into how differences across online social spaces may impact political polarization.

Social media are utilized by millions of citizens to discuss important political issues. Politicians use these platforms to connect with the public and broadcast policy positions. Therefore, data from social media has enabled many studies of political discussion. While most analyses are limited to data from individual platforms, people are embedded in a larger information ecosystem spanning multiple social networks. Here we describe and provide access to the Indiana University 2022 U.S. Midterms Multi-Platform Social Media Dataset (MEIU22), a collection of social media posts from Twitter, Facebook, Instagram, Reddit, and 4chan. MEIU22 links to posts about the midterm elections based on a comprehensive list of keywords and tracks the social media accounts of 1,011 candidates from October 1 to December 25, 2022. We also publish the source code of our pipeline to enable similar multi-platform research projects.