Prior Ideological Landscape

Prior ideological landscape research aims to quantify and understand pre-existing societal divisions that influence responses to events. Current methods leverage large language models (LLMs) and graph neural networks to analyze vast text corpora (e.g., parliamentary speeches, social media posts) and identify ideological positions, often using techniques like semantic scaling and embedding distance calculations. This work is significant for improving social science measurement, enabling more accurate predictions of societal reactions to events, and offering insights into the dynamics of polarization and echo chambers.