Detecting latent ideology in expert text: Evidence from academic papers in economics

Previous work on extracting ideology from text has focused on domains where expression of political views is expected, but it’s unclear if current technology can work in domains where displays of ide-ology are considered inappropriate. We present a supervised ensemble n-gram model for ideology extraction with topic adjustments and apply it to one such do-main: research papers written by academic economists. We show economists ’ polit-ical leanings can be correctly predicted, that our predictions generalize to new do-mains, and that they correlate with public policy-relevant research findings. We also present evidence that unsupervised models can under-perform in domains where ide-ological expression is discouraged.