Political Ideology and Polarization of Policy Positions: A Multi-dimensional Approach
This work addresses the need for nuanced ideological analysis in political science, offering a novel dataset and method for researchers studying polarization, though it is incremental in building on existing stance detection research.
The paper tackles the problem of analyzing political ideology and polarization by introducing a multi-dimensional approach and a diachronic dataset of news articles annotated by experts, enabling quantitative and temporal measurement of polarization as ideological distance.
Analyzing ideology and polarization is of critical importance in advancing our grasp of modern politics. Recent research has made great strides towards understanding the ideological bias (i.e., stance) of news media along the left-right spectrum. In this work, we instead take a novel and more nuanced approach for the study of ideology based on its left or right positions on the issue being discussed. Aligned with the theoretical accounts in political science, we treat ideology as a multi-dimensional construct, and introduce the first diachronic dataset of news articles whose ideological positions are annotated by trained political scientists and linguists at the paragraph level. We showcase that, by controlling for the author's stance, our method allows for the quantitative and temporal measurement and analysis of polarization as a multidimensional ideological distance. We further present baseline models for ideology prediction, outlining a challenging task distinct from stance detection.