Generalizability of Media Frames: Corpus creation and analysis across countries

2025-06-19

AI Summary

This study investigates the cross-cultural applicability of the Media Frame Corpus (MFC) framework beyond English and U.S. contexts, focusing on political-economic news in Brazilian Portuguese. Method: We construct FrameNews-PT—the first annotated corpus for this language—following MFC guidelines, conduct multiple rounds of expert annotation, and perform rigorous inter-annotator agreement assessment. Contribution/Results: Systematic validation confirms that all 15 MFC frames are broadly applicable, requiring only minor guideline adaptations. We identify a “fallback” phenomenon wherein annotators consistently resort to generic frames for emerging topics, revealing dependency on broad conceptual categories. Zero-shot cross-lingual transfer of language models underperforms fine-tuned baselines, underscoring the critical role of context-sensitive, culturally grounded annotation. The study proposes that cross-cultural frame application necessitates adaptive refinement aligned with local semantic practices, establishing both a methodological paradigm and an empirical benchmark for global media framing research.

Technology Category

• Natural Language Processing: Machine Translation, Multilinguality, Cross-Lingual NLP
• Application Domains: Humanities & Computational Social Science
• Multiagent Systems: Agreement, Argumentation & Negotiation

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Economics, Online Markets and Human Computation: Humans versus LLMs for data annotation and labeling

Abstract

Frames capture aspects of an issue that are emphasized in a debate by interlocutors and can help us understand how political language conveys different perspectives and ultimately shapes people's opinions. The Media Frame Corpus (MFC) is the most commonly used framework with categories and detailed guidelines for operationalizing frames. It is, however, focused on a few salient U.S. news issues, making it unclear how well these frames can capture news issues in other cultural contexts. To explore this, we introduce FrameNews-PT, a dataset of Brazilian Portuguese news articles covering political and economic news and annotate it within the MFC framework. Through several annotation rounds, we evaluate the extent to which MFC frames generalize to the Brazilian debate issues. We further evaluate how fine-tuned and zero-shot models perform on out-of-domain data. Results show that the 15 MFC frames remain broadly applicable with minor revisions of the guidelines. However, some MFC frames are rarely used, and novel news issues are analyzed using general'fall-back'frames. We conclude that cross-cultural frame use requires careful consideration.

Problem

• Assess generalizability of US media frames in other cultures
• Create annotated dataset for Brazilian Portuguese news analysis
• Evaluate frame adaptation and model performance across domains

Innovation

• FrameNews-PT dataset for Brazilian Portuguese news
• Evaluating MFC frames' cross-cultural generalizability
• Testing fine-tuned and zero-shot models' performance