Predicting Narratives of Climate Obstruction in Social Media Advertising (2024.findings-acl)
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| Challenge: | Social media advertising allows entities to construct narratives that align with their commercial interests and sway public perception. |
| Approach: | They propose to classify climate-related narratives into seven categories based on existing definitions and data. |
| Outcome: | The proposed method outperforms other methods and can reduce human annotation costs. |
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| Challenge: | a new study examines the fine-grained classification and classification of climate change-related social media text. |
| Approach: | They propose to use two datasets to analyze climate change-related social media text and propose a fine-grained classification based on the proposed dataset. |
| Outcome: | The proposed datasets are compared with existing datasets and benchmarked using the best-performing model. |
Analyzing the Dynamics of Climate Change Discourse on Twitter: A New Annotated Corpus and Multi-Aspect Classification (2024.lrec-main)
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Shuvam Shiwakoti, Surendrabikram Thapa, Kritesh Rauniyar, Akshyat Shah, Aashish Bhandari, Usman Naseem
| Challenge: | a lack of data on climate change discourse has highlighted the need for further advancement . a new study examines the discourse on social media platforms that ignores climate change . |
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A Structured Clustering Approach for Inducing Media Narratives (2026.acl-long)
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| Challenge: | Existing approaches to modeling media narratives miss subtle narrative patterns through coarse-grained analysis or require domain-specific taxonomies that limit scalability. |
| Approach: | They propose a framework for inducing rich narrative schemas by jointly modeling events and characters via structured clustering. |
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Post-hoc Study of Climate Microtargeting on Social Media Ads with LLMs: Thematic Insights and Fairness Evaluation (2025.findings-emnlp)
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| Challenge: | Climate change communication on social media increasingly employs microtargeting strategies to effectively reach and influence specific demographic groups. |
| Approach: | They analyze social media ads using large language models to examine their performance . they find that LLMs perform well overall, but certain biases exist . |
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Actors, Frames and Arguments: A Multi-Decade Computational Analysis of Climate Discourse in Financial News using Large Language Models (2026.findings-eacl)
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| 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. |
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Automated Detection of Tropes In Short Texts (2025.coling-main)
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| Challenge: | Tropes are often used in movies to convey familiar patterns, but they also play a significant role in online communication . |
| Approach: | They propose to automatically detect tropes in social media posts by using a dataset . they define the task, distinguish it from previous work, and develop a machine learning technique . |
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Can LLMs Learn Macroeconomic Narratives from Social Media? (2025.findings-naacl)
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| Challenge: | Existing evaluation strategies for analyzing economic data with narratives are limited due to the complexity of the interplay of numerous factors and the difficulty in isolating causal relationships. |
| Approach: | They propose to use two Twitter datasets to capture economy-related narratives and use them to construct models using large language models. |
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Narrative Media Framing in Political Discourse (2025.findings-acl)
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| 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 . |
EcoVerse: An Annotated Twitter Dataset for Eco-Relevance Classification, Environmental Impact Analysis, and Stance Detection (2024.lrec-main)
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| Challenge: | EcoVerse is an annotated English Twitter dataset of 3,023 tweets . mainstream NLP tasks dominate the scene, but environmental impacts remain unstudied . |
| Approach: | They propose an annotation scheme for Eco-Relevance Classification, Stance Detection and an original approach for Environmental Impact Analysis. |
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Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media (2025.acl-long)
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| Challenge: | Social media platforms are experiencing a growing presence of AI-Generated Texts (AIGTs) however, the misuse of AIGTs could have profound implications for public opinion . |
| Approach: | They collect a dataset with 2.4M posts from 3 major social media platforms . they then construct a diverse dataset to train and evaluate AIGT detectors . |
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