Political Ideology and Polarization of Policy Positions: A Multi-dimensional Approach
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 54 references that are in the map. First posted on arXiv 28 Jun 2021.
Builds on
6 of 54 references.
References · 6
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2020We Can Detect Your Bias: Predicting the Political Ideology of News Articlescited by 92
- 2020Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularitycited by 32
- 2018Multi-view Models for Political Ideology Detection of News Articlescited by 27
- 2019Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Mediacited by 26
- 2019Adaptive Ensembling: Unsupervised Domain Adaptation for Political Document Analysiscited by 4
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