Detecting Latent Ideology in Expert Text: Evidence From Academic Papers in Economics

Zubin Jelveh, Bruce Kogut, Suresh Naidu

Abstract: 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 ideology are considered inappropriate. We present a supervised ensemble n-gram model for ideology extraction with topic adjustments and apply it to one such domain: research papers written by academic economists. We show economists’ political leanings can be correctly predicted, that our predictions generalize to new domains, and that they correlate with public policy-relevant research findings. We also present evidence that unsupervised models can under-perform in domains where ideological expression is discouraged.