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# Dataset Card

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This dataset contains 100 manually annotated narratives of climate change appearing in the USA news. Apart from the narrative frames annotation, we include their narrative components, as well as generic frames, political leaning and outlet.

## Dataset Details

Please refer to our paper and other resources for the details of annotation, taxonomy, model performance on the dataset etc: 

- **Paper [to appear in ACL 2025 Findings]:** https://arxiv.org/pdf/2506.00737
- **Repository:** https://github.com/julia-nixie/narratives
- **Demo:** https://julia-nixie.github.io/narratives

## Dataset Structure

The dataset has the following fields (please refer to our paper for the lists of possible values and their descriptions):

**NARRATIVE**: the overall narrative frame of the article

**HERO**: the main hero of the narrative

**VILLAIN**: the main villain of the narrative

**VICTIM**: the main victim of the narrative

**FOCUS**: who (hero, villain, or victim) the narrative is focusing on

**CONFLICT**: shows if the narrative fuels a particular conflict or problem (such as climate change), fuels its resolution, or prevents either conflict or resolution

**STORY**: shows if the narrative is individualistic, hierarchical, or egalitarian

**ARTICLE**: full text of the article

**outlet**: the outlet of the article

**leaning**: the political leaning of the outlet

**CO**: if the article has the generic "Conflict" frame

**RE**: if the article has the generic "Resolution" frame

**HI**: if the article has the generic "Human Interest" frame

**EC**: if the article has the generic "Economic" frame

**MO**: if the article has the generic "Morality" frame


## Citation

Please cite our paper if you use the dataset:

**BibTeX:**

@article{otmakhova2025narrative,
  title={Narrative Media Framing in Political Discourse},
  author={Otmakhova, Yulia and Frermann, Lea},
  journal={arXiv preprint arXiv:2506.00737},
  year={2025}
}


## Dataset Card Contact

Please contact us at y.otmakhova@unimelb.edu.au if you have any questions regarding the dataset.