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 an unsupervised method to quantify latent narrative structures in text documents. Our new software package relatio identifies coherent entity groups and maps explicit relations between them in the text. 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.

Relatio: text semantics capture political and economic narratives

Ash, Elliott;Gauthier, Germain
2024

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 an unsupervised method to quantify latent narrative structures in text documents. Our new software package relatio identifies coherent entity groups and maps explicit relations between them in the text. 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.
2024
2023
Widmer, Philine; Ash, Elliott; Gauthier, Germain
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4066039
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