  Estimating the political leanings of social media users is a challenging and
ever more pressing problem given the increase in social media consumption. We
introduce Retweet-BERT, a simple and scalable model to estimate the political
leanings of Twitter users. Retweet-BERT leverages the retweet network structure
and the language used in users' profile descriptions. Our assumptions stem from
patterns of networks and linguistics homophily among people who share similar
ideologies. Retweet-BERT demonstrates competitive performance against other
state-of-the-art baselines, achieving 96%-97% macro-F1 on two recent Twitter
datasets (a COVID-19 dataset and a 2020 United States presidential elections
dataset). We also perform manual validation to validate the performance of
Retweet-BERT on users not in the training data. Finally, in a case study of
COVID-19, we illustrate the presence of political echo chambers on Twitter and
show that it exists primarily among right-leaning users. Our code is
open-sourced and our data is publicly available.
