mlsanityData to 7 Oct 2026

Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media

arXiv 2009.09609 ↗First posted 21 Sep 2020cs.CL cs.AI cs.CYcited by 27

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Abstract (arXiv)

In this paper we suggest a minimally-supervised approach for identifying nuanced frames in news article coverage of politically divisive topics. We suggest to break the broad policy frames suggested by Boydstun et al., 2014 into fine-grained subframes which can capture differences in political ideology in a better way. We evaluate the suggested subframes and their embedding, learned using minimal supervision, over three topics, namely, immigration, gun-control and abortion. We demonstrate the ability of the subframes to capture ideological differences and analyze political discourse in news media.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Sep 2020.

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Citing papers per year: 2021: 5; 2022: 4; 2023: 6; 2024: 6; 2025: 4; 2026: 2.

27 papers.

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  1. 2023Can Large Language Models Transform Computational Social Science?cited by 245
  2. 2024Measuring Political Bias in Large Language Models: What Is Said and How It Is Saidcited by 89
  3. 2021A Survey of Race, Racism, and Anti-Racism in NLPcited by 74
  4. 2021Modeling Framing in Immigration Discourse on Social Mediacited by 37
  5. 2021Identifying Morality Frames in Political Tweets using Relational Learningcited by 26
  6. 2021To Protect and To Serve? Analyzing Entity-Centric Framing of Police Violencecited by 12
  7. 2022Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Mediacited by 10
  8. 2021Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsitycited by 9
  9. 2022Weakly Supervised Learning for Analyzing Political Campaigns on Facebookcited by 8
  10. 2023Predicting Sentence-Level Factuality of News and Bias of Media Outletscited by 6
  11. 2023Towards Few-Shot Identification of Morality Frames using In-Context Learningcited by 6
  12. 2023Connecting the Dots in News Analysis: Bridging the Cross-Disciplinary Disparities in Media Bias and Framingcited by 6
15 more
  1. 2024Media Framing through the Lens of Event-Centric Narrativescited by 5
  2. 2025Framing Political Bias in Multilingual LLMs Across Pakistani Languagescited by 5
  3. 2022From Hesitancy Framings to Vaccine Hesitancy Profiles: A Journey of Stance, Ontological Commitments and Moral Foundationscited by 4
  4. 2023"A Tale of Two Movements": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Predictioncited by 4
  5. 2024Exploring Factual Entailment with NLI: A News Media Studycited by 4
  6. 2024Framing in the Presence of Supporting Data: A Case Study in U.S. Economic Newscited by 2
  7. 2025Retain or Reframe? A Computational Framework for the Analysis of Framing in News Articles and Reader Commentscited by 2
  8. 2022Unsupervised Detection of Contextualized Embedding Bias with Application to Ideologycited by 1
  9. 2023Towards Corpus-Scale Discovery of Selection Biases in News Coverage: Comparing What Sources Say About Entities as a Startcited by 1
  10. 2025Journalism-Guided Agentic In-Context Learning for News Stance Detectioncited by 1
  11. 2024DocNet: Semantic Structure in Inductive Bias Detection Modelscited by 0
  12. 2024Paired Completion: Flexible Quantification of Issue-framing at Scale with LLMscited by 0
  13. 2025Visual moral inference and communicationcited by 0
  14. 2026Paid Voices vs. Public Feeds: Interpretable Cross-Platform Theme-Based Analysis of Climate Discoursecited by 0
  15. 2026Discovering Conceptual Metaphors Across Topics and Media Typescited by 0