Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity (2022.findings-naacl)
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| Challenge: | Existing methods to detect ideological divides in social media rely on knowing in advance the political orientation of text . fascist and mainstream are among the most polarized concepts in reddit in 2019 . |
| Approach: | They propose a minimally supervised method that leverages the network structure of online discussion forums to detect polarized concepts. |
| Outcome: | The proposed framework captures temporal ideological dynamics such as right-wing and left-wing radicalization using graph neural networks and sparsity learning. |
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Jaspreet Ranjit, Brihi Joshi, Rebecca Dorn, Laura Petry, Olga Koumoundouros, Jayne Bottarini, Peichen Liu, Eric Rice, Swabha Swayamdipta
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Predicting the Topical Stance and Political Leaning of Media using Tweets (2020.acl-main)
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| Challenge: | Existing methods for determining stances of media outlets and influential people are expensive. |
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