Relatio : Text Semantics Capture Political and Economic Narratives – ERRATUM

Abstract

Social scientists have become increasingly interested in how narratives -- the stories in fiction, politics, and life -- shape beliefs, behavior, and government policies. This paper provides a novel, unsupervised method to quantify latent narrative structures in text, drawing on computational linguistics tools for clustering coherent entity groups and capturing relations between them. After validating the method, we provide an application to the U.S. Congressional Record to analyze political and economic narratives in recent decades. Our analysis highlights the dynamics, sentiment, polarization, and interconnectedness of narratives in political discourse.