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 .

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Challenge: Existing studies on media framing have focused on English only data, leaving a gap in research concerning multilingual contexts.
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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.
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Entity Framing and Role Portrayal in the News (2025.findings-acl)

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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 .
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OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data (2021.emnlp-demo)

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Challenge: Existing frameworks for analyzing frames in multilingual text documents are available online and via an API.
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Multilingual Multifaceted Understanding of Online News in Terms of Genre, Framing, and Persuasion Techniques (2023.acl-long)

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Challenge: a new dataset of news articles is presented that covers genre, framing, and persuasion techniques.
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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.
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Uncovering Temporal Framing in the News (2026.acl-long)

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Challenge: Temporal language is used to structure meaning rather than report chronology in news discourse . a recent study focused on temporal expression extraction and temporal reasoning .
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PolyNarrative: A Multilingual, Multilabel, Multi-domain Dataset for Narrative Extraction from News Articles (2025.acl-long)

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Challenge: a new dataset of news articles annotated for narratives provides a framework for narrative detection . recurring narratives can propagate with very high velocity across audiences, languages and countries .
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Cross-lingual Structure Transfer for Zero-resource Event Extraction (2020.lrec-1)

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Challenge: Existing approaches for information extraction only use name tagging . Currently, most successful cross-lingual transfer learning methods are limited to sequence labeling .
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