Challenge: Human Interest (HI) framing is a narrative strategy that injects news stories with a relatable, emotional angle and a human face to engage the audience.
Approach: They perform a systematic analysis of HI stories to understand its role in climate change reporting in English-speaking countries from four continents.
Outcome: The proposed approach has shown to capture and retain readership and enhance political engagement of the population.

Similar Papers

A Study on Scaling Up Multilingual News Framing Analysis (2024.findings-naacl)

Copied to clipboard

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 .
Narratives at Conflict: Computational Analysis of News Framing in Multilingual Disinformation Campaigns (2024.acl-srw)

Copied to clipboard

Challenge: Existing methods for multilingual framing differ from those used in English-speaking world . framers often use loaded vocabularies to create political images or favor a particular point of view .
Approach: They use eight years of Russian-backed disinformation campaigns to examine framing . they find that disinformation campaign consistently favors specific framers .
Outcome: The proposed method underperforms and shows high disagreements in Russian-language articles . the proposed method is based on eight years of Russian-backed disinformation campaigns .
Narrative Media Framing in Political Discourse (2025.findings-acl)

Copied to clipboard

Challenge: Narrative frames are a powerful way of conceptualizing and communicating complex ideas.
Approach: They propose a framework which formalizes and operationalizes elements of narrative framing . they annotate news articles in the climate change domain and test their framework .
Outcome: The proposed framework formalizes and operationalizes elements of narrative framing . it is applied to climate change crisis data, showing generalizability of the framework .
What Media Frames Reveal About Stance: A Dataset and Study about Memes in Climate Change Discourse (2025.findings-emnlp)

Copied to clipboard

Challenge: Media framing is a method of shaping public perceptions of issues, but the interaction between stance and media frame remains unexplored.
Approach: They propose to use a dataset of climate-change memes annotated with stance and media frames to conceptualize and computationally explore this interaction.
Outcome: The proposed dataset includes 1,184 climate-change memes sourced from 47 subreddits and enables analysis of frame prominence over time and communities.
Ideological Knowledge Representation: Framing Climate Change in EcoLexicon (2024.lrec-main)

Copied to clipboard

Challenge: a method to extract ideological knowledge from corpora is proposed to represent environmental concepts and terms in terminological resources . political discourse is not considered specialized language, but politicians use scientific terms to soften the message .
Approach: They propose to use terminological knowledge bases to represent political discourse on environmental concepts and terms.
Outcome: The proposed method shows how climate change discourse changes across ideological spectrum . it uses spanish and english parliamentary debates to extract ideological knowledge from corpora.
Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing (2023.acl-long)

Copied to clipboard

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.
“Again, Dozens of Refugees Drowned”: A Computational Study of Political Framing Evoked by Presuppositions (2022.naacl-srw)

Copied to clipboard

Challenge: Earlier studies on issue framing have focused heavily on shallow classification of issue framers, while framerical cues remain neglected.
Approach: They take presupposition-triggering adverbs such as ‘again’ as a study case and examine how different German newspapers use them to covertly evoke different attitudinal subtexts.
Outcome: The findings show that iterative adverbs like 'again' can act as subtle but effective cues of framing.
Manovaad: A Novel Approach to Event Oriented Corpus Creation Capturing Subjectivity and Focus (2020.lrec-1)

Copied to clipboard

Challenge: Several studies conducted on the different styles of reporting in journalism are essential in understanding phenomena such as media bias and multiple interpretations of the same event.
Approach: They propose a novel method of event reporting that correlates the degree of subjectivity with the geographical closeness of reporting using a Bi-RNN model.
Outcome: The proposed method correlates the degree of subjectivity with the geographical closeness of reporting using a Bi-RNN model.
Media Attitude Detection via Framing Analysis with Events and their Relations (2024.emnlp-main)

Copied to clipboard

Challenge: a recent study examined the effects of media framing on public perception and understanding of news articles.
Approach: They propose to extract framing devices employed by media to assess their role in framating the narrative.
Outcome: The proposed method surpasses baseline models and offers a more detailed and explainable analysis of media framing effects.
Actors, Frames and Arguments: A Multi-Decade Computational Analysis of Climate Discourse in Financial News using Large Language Models (2026.findings-eacl)

Copied to clipboard

Challenge: a new study examines how financial news media portrays climate change . financial news is the nervous system of the global economy .
Approach: They propose a three-stage Actor–Frame–Argument pipeline that uses large language models to extract actors, stances, frames, and argumentative structures from a 980,061-article corpus.
Outcome: The proposed pipeline extracts actors, stances, frames, and argumentative structures from a 980,061-article corpus of climate-related financial news from the Dow Jones Newswire (2000–2023) it is based on a human-annotated gold standard and a Decompositional Verification Framework (DVF) that decomposes evaluation into completeness, faithfulness, coherence, and relevance, with multi-judge scoring calibrated against human ratings.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations