Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames (2021.naacl-main)
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| Challenge: | Existing models for news analysis lack transparency in their predictions. |
| Approach: | They propose a semi-supervised model that embeds local information into news articles . it can be used to improve automatic news analysis, authors argue . |
| Outcome: | The proposed model outperforms previous models and can be used with unlabeled training data. |
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Multi-Modal Framing Analysis of News (2025.emnlp-main)
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| Challenge: | Automated frame analysis of political communication has been limited by the use of predefined frames and the visual contexts in which they appear. |
| Approach: | They propose a method for doing multi-modal, multi-label framing analysis at scale using large (vision-) language models. |
| Outcome: | The proposed method provides a more complete picture for understanding media bias. |
CLoSE: Contrastive Learning of Subframe Embeddings for Political Bias Classification of News Media (2022.coling-1)
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| Challenge: | Framing is a political strategy in which journalists and politicians emphasize certain aspects of an issue to influence and sway public opinion. |
| Approach: | They propose a BERT-based model which embeds indicators of frames from news articles in order to predict political bias. |
| Outcome: | The proposed model performs on subframes and political bias classification tasks and is able to detect political bias on both zero-shot and few-shot learning tasks. |
Multi-Label and Multilingual News Framing Analysis (2020.acl-main)
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| Challenge: | Recent studies have focused on news framing in English, but few studies have explored how it can be extended to other languages and in multi-label settings. |
| Approach: | They propose a method that leverages dictionary and few annotations to detect frames from just the headline in a low-resource context. |
| Outcome: | The proposed method performs better than translating the entire headline to the source language . it can be scaled up to many languages, even those without existing translation technologies . |
Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Media (2020.emnlp-main)
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| Challenge: | a new study suggests a minimally supervised approach for identifying nuanced political frames in news articles on politically divisive topics. |
| Approach: | They propose a minimally supervised approach for identifying nuanced policy frames in news coverage of politically divisive topics. |
| Outcome: | The proposed subframes can capture differences in political ideology better . the proposed frameworks were tested on immigration, gun control and abortion topics . |
A Study on Scaling Up Multilingual News Framing Analysis (2024.findings-naacl)
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| Challenge: | Existing studies on media framing have focused on English only data, leaving a gap in research concerning multilingual contexts. |
| Approach: | They propose to use crowd-sourced datasets to automate framing analysis by automating translation and annotation. |
| Outcome: | The proposed system improves on existing models in Bengali and Portuguese . the proposed system can train on a crowd-sourced dataset in 12 languages . |
OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data (2021.emnlp-demo)
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Vibhu Bhatia, Vidya Prasad Akavoor, Sejin Paik, Lei Guo, Mona Jalal, Alyssa Smith, David Assefa Tofu, Edward Edberg Halim, Yimeng Sun, Margrit Betke, Prakash Ishwar, Derry Tanti Wijaya
| Challenge: | Existing frameworks for analyzing frames in multilingual text documents are available online and via an API. |
| Approach: | They propose a web-based system for analyzing frames in multilingual text documents . framework combines unsupervised and supervised machine learning and leverages a state-of-the-art multilingual language model . |
| Outcome: | The proposed framework can significantly improve frame prediction performance while requiring a small sample of manual annotations. |
Controlled Neural Sentence-Level Reframing of News Articles (2021.findings-emnlp)
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| Challenge: | a news article is framed from a specific perspective, but reframing can be difficult . a framed article can be used to communicate with opposing camps of audiences . |
| Approach: | They propose to reframe news articles using a media frame corpus to achieve this . they propose three strategies to train neural models for reframing . |
| Outcome: | The proposed techniques maintain coherence of sentences and reframe them correctly . the proposed techniques are effective but have tradeoffs . |
Entity Framing and Role Portrayal in the News (2025.findings-acl)
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Tarek Mahmoud, Zhuohan Xie, Dimitar Iliyanov Dimitrov, Nikolaos Nikolaidis, Purificação Silvano, Roman Yangarber, Shivam Sharma, Elisa Sartori, Nicolas Stefanovitch, Giovanni Da San Martino, Jakub Piskorski, Preslav Nakov
| Challenge: | a dataset of news articles containing 22 fine-grained characters is annotated for entity framing and role portrayal . the dataset includes 1,378 recent news articles in five languages focusing on the Ukraine-Russia War and climate change . |
| Approach: | They propose a multilingual and hierarchical corpus annotated for entity framing and role portrayal in news articles. |
| Outcome: | The proposed dataset includes 1,378 recent news articles in five languages focusing on the Ukraine-Russia War and climate change . the authors report evaluation results on state-of-the-art multilingual transformers and hierarchical zero-shot learning using LLMs at the level of a document, paragraph, and sentence . |
Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing (2023.acl-long)
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| Challenge: | a growing body of work attempts to automatically detect media frames in the news or social media, but most adopts a topic-like view on frames, evading modelling the broader document-level narrative. |
| Approach: | They propose an annotation paradigm that breaks a complex annotation task into a series of simple binary questions. |
| Outcome: | The proposed method is both effective and transparent in its predictions. |
Issue Framing in Online Discussion Fora (N19-1)
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| Challenge: | In online discussion fora, speakers often make arguments by highlighting certain aspects of the topic. |
| Approach: | They propose to use a newswire and social media annotated corpus to detect issue frames in online discussions. |
| Outcome: | The proposed model can be applied to the domain of discussion fora using multi-task and adversarial training. |