Using Language Models for Classifying the Party Affiliation of Political Texts

We analyze the use of language models for political text classification. Political texts become increasingly available and language models have succeeded in various natural language processing tasks. We apply two baselines and different language models to data from the UK, Germany, and Norway. Observed accuracy shows language models improving on the performance of the baselines by up to 10.35% (Norwegian), 12.95% (German), and 6.39% (English).