Language model estimates indicate increased outgroup animosity among a sample of politicians, journalists, and partisan users on Twitter and Reddit

Using language models, we analyze a sample of 67 million tweets and 30 million Reddit comments from 2010 to 2023 from partisan users, journalists, and politicians. Our analysis focused on posts referencing at least one of 215 left- or right-leaning political entities, excluding those referencing entities on both sides. In this sample of posts, we found that estimates of outgroup animosity rose among partisan users, politicians, and journalists, with newer cohorts expressing higher levels of animosity than previous ones. Moreover, a small fraction of users is responsible for a disproportionate share of this negative content. We observe systematic differences in topic-level outgroup affect across political orientations: right-leaning users are twice as likely to exhibit outgroup animosity when discussing immigration, while left-leaning users show heightened outgroup animosity when discussing healthcare. On Twitter, U.S. politicians on the left exhibit more outgroup animosity than partisan users in our sample, but from 2017 to 2023, politicians on the right have experienced the sharpest rise in estimated outgroup animosity, surpassing journalists, media, and partisan users. On Reddit, a small number of communities account for a large share of polarizing rhetoric, with the rise and eventual ban of r/TheDonald significantly shaping trends in polarizing discourse among politically active right-leaning users.